Nonlinear Image Interpolation Through Extended Permutation Filters. - Deva Ramanan; Kenneth E. Barner (ICIP, 2000)

Finding and Tracking People from the Bottom Up. - Deva Ramanan; David A. Forsyth (CVPR (2), 2003)

Using Temporal Coherence to Build Models of Animals. - Deva Ramanan; David A. Forsyth (ICCV, 2003)

Automatic Annotation of Everyday Movements. - Deva Ramanan; David A. Forsyth (NIPS, 2003)

Detecting, Localizing and Recovering Kinematics of Textured Animals. - Deva Ramanan; David A. Forsyth; Kobus Barnard (CVPR (2), 2005)

Strike a Pose: Tracking People by Finding Stylized Poses. - Deva Ramanan; David A. Forsyth; Andrew Zisserman (CVPR (1), 2005)

Tracking People and Recognizing Their Activities. - Deva Ramanan; David A. Forsyth; Andrew Zisserman (CVPR (2), 2005)

Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis. - David A. Forsyth; Okan Arikan; Leslie Ikemoto; James F. O'Brien; Deva Ramanan (Found. Trends Comput. Graph. Vis., 2005)

Training Deformable Models for Localization. - Deva Ramanan; Cristian Sminchisescu (CVPR (1), 2006)

Learning to parse images of articulated bodies. - Deva Ramanan (NIPS, 2006)

Building Models of Animals from Video. - Deva Ramanan; David A. Forsyth; Kobus Barnard (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

Using Segmentation to Verify Object Hypotheses. - Deva Ramanan (CVPR, 2007)

Leveragingarchivalvideo for building face datasets. - Deva Ramanan; Simon Baker; Sham M. Kakade (ICCV, 2007)

Assessment of Post-Stroke Functioning Using Machine Vision. - Sonya Allin; Deva Ramanan (MVA, 2007)

Tracking People by Learning Their Appearance. - Deva Ramanan; David A. Forsyth; Andrew Zisserman (IEEE Trans. Pattern Anal. Mach. Intell., 2007)

A discriminatively trained, multiscale, deformable part model. - Pedro F. Felzenszwalb; David A. McAllester; Deva Ramanan (CVPR, 2008)

Increasing the density of Active Appearance Models. - Krishnan Ramnath; Simon Baker; Iain A. Matthews; Deva Ramanan (CVPR, 2008)

Bilinear classifiers for visual recognition. - Hamed Pirsiavash; Deva Ramanan; Charless C. Fowlkes (NIPS, 2009)

Discriminative models for static human-object interactions. - Chaitanya Desai; Deva Ramanan; Charless C. Fowlkes (CVPR Workshops, 2010)

Layered object detection for multi-class segmentation. - Yi Yang 007; Sam Hallman; Deva Ramanan; Charless C. Fowlkes (CVPR, 2010)

Multiresolution Models for Object Detection. - Dennis Park; Deva Ramanan; Charless C. Fowlkes (ECCV (4), 2010)

Efficiently Scaling Up Video Annotation with Crowdsourced Marketplaces. - Carl Vondrick; Deva Ramanan; Donald J. Patterson (ECCV (4), 2010)

Discriminative Latent Variable Models for Object Detection. - Pedro F. Felzenszwalb; Ross B. Girshick; David A. McAllester; Deva Ramanan (ICML, 2010)

SEMARTCam scheduler: semantics driven real-time data collection from indoor camera networks to maximize event detection. - Ronen Vaisenberg; Sharad Mehrotra; Deva Ramanan (J. Real Time Image Process., 2010)

Object Detection with Discriminatively Trained Part-Based Models. - Pedro F. Felzenszwalb; Ross B. Girshick; David A. McAllester; Deva Ramanan (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Part-Based Models for Finding People and Estimating Their Pose. - Deva Ramanan (Visual Analysis of Humans, 2011)

AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video. - Sangmin Oh; Anthony Hoogs; A. G. Amitha Perera; Naresh P. Cuntoor; Chia-Chih Chen; Jong Taek Lee; Saurajit Mukherjee; J. K. Aggarwal; Hyungtae Lee; Larry S. Davis; Eran Swears; Xiaoyang Wang 001; et al. (AVSS, 2011)

Where's Waldo: Matching people in images of crowds. - Rahul Garg 002; Steven M. Seitz; Deva Ramanan; Noah Snavely (CVPR, 2011)

A large-scale benchmark dataset for event recognition in surveillance video. - Sangmin Oh; Anthony Hoogs; A. G. Amitha Perera; Naresh P. Cuntoor; Chia-Chih Chen; Jong Taek Lee; Saurajit Mukherjee; J. K. Aggarwal; Hyungtae Lee; Larry S. Davis; Eran Swears; Xiaoyang Wang 001; et al. (CVPR, 2011)

Globally-optimal greedy algorithms for tracking a variable number of objects. - Hamed Pirsiavash; Deva Ramanan; Charless C. Fowlkes (CVPR, 2011)

Articulated pose estimation with flexible mixtures-of-parts. - Yi Yang 007; Deva Ramanan (CVPR, 2011)

N-best maximal decoders for part models. - Dennis Park; Deva Ramanan (ICCV, 2011)

Statistical Tests for Optimization Efficiency. - Levi Boyles; Anoop Korattikara Balan; Deva Ramanan; Max Welling (NIPS, 2011)

Video Annotation and Tracking with Active Learning. - Carl Vondrick; Deva Ramanan (NIPS, 2011)

Discriminative Models for Multi-Class Object Layout. - Chaitanya Desai; Deva Ramanan; Charless C. Fowlkes (Int. J. Comput. Vis., 2011)

Local Distance Functions: A Taxonomy, New Algorithms, and an Evaluation. - Deva Ramanan; Simon Baker (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Do We Need More Training Data or Better Models for Object Detection?. - Xiangxin Zhu; Carl Vondrick; Deva Ramanan; Charless C. Fowlkes (BMVC, 2012)

Detecting activities of daily living in first-person camera views. - Hamed Pirsiavash; Deva Ramanan (CVPR, 2012)

Steerable part models. - Hamed Pirsiavash; Deva Ramanan (CVPR, 2012)

Recognizing proxemics in personal photos. - Yi Yang 007; Simon Baker; Anitha Kannan; Deva Ramanan (CVPR, 2012)

Face detection, pose estimation, and landmark localization in the wild. - Xiangxin Zhu; Deva Ramanan (CVPR, 2012)

Detecting Actions, Poses, and Objects with Relational Phraselets. - Chaitanya Desai; Deva Ramanan (ECCV (4), 2012)

Discriminative Decorrelation for Clustering and Classification. - Bharath Hariharan; Jitendra Malik; Deva Ramanan (ECCV (4), 2012)

Analyzing 3D Objects in Cluttered Images. - Mohsen Hejrati; Deva Ramanan (NIPS, 2012)

Layered Object Models for Image Segmentation. - Yi Yang 007; Sam Hallman; Deva Ramanan; Charless C. Fowlkes (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Predicting Functional Regions on Objects. - Chaitanya Desai; Deva Ramanan (CVPR Workshops, 2013)

Exploring Weak Stabilization for Motion Feature Extraction. - Dennis Park; C. Lawrence Zitnick; Deva Ramanan; Piotr Dollár (CVPR, 2013)

Histograms of Sparse Codes for Object Detection. - Xiaofeng Ren; Deva Ramanan (CVPR, 2013)

Self-Paced Learning for Long-Term Tracking. - James Steven Supancic III; Deva Ramanan (CVPR, 2013)

Visual object detection with deformable part models. - Pedro F. Felzenszwalb; Ross B. Girshick; David A. McAllester; Deva Ramanan (Commun. ACM, 2013)

Dual coordinate solvers for large-scale structural SVMs. - Deva Ramanan (CoRR, 2013)

Egovision4Health - Assessing Activities of Daily Living from a Wearable RGB-D Camera for In-Home Health Care Applications. - Grégory Rogez; Deva Ramanan; J. M. M. Montiel (ERCIM News, 2013)

Efficiently Scaling up Crowdsourced Video Annotation - A Set of Best Practices for High Quality, Economical Video Labeling. - Carl Vondrick; Donald J. Patterson; Deva Ramanan (Int. J. Comput. Vis., 2013)

Articulated Human Detection with Flexible Mixtures of Parts. - Yi Yang 007; Deva Ramanan (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Parsing Occluded People. - Golnaz Ghiasi; Yi Yang 007; Deva Ramanan; Charless C. Fowlkes (CVPR, 2014)

Analysis by Synthesis: 3D Object Recognition by Object Reconstruction. - Mohsen Hejrati; Deva Ramanan (CVPR, 2014)

Parsing Videos of Actions with Segmental Grammars. - Hamed Pirsiavash; Deva Ramanan (CVPR, 2014)

Capturing Long-Tail Distributions of Object Subcategories. - Xiangxin Zhu; Dragomir Anguelov; Deva Ramanan (CVPR, 2014)

Microsoft COCO: Common Objects in Context. - Tsung-Yi Lin; Michael Maire; Serge J. Belongie; James Hays; Pietro Perona; Deva Ramanan; Piotr Dollár; C. Lawrence Zitnick (ECCV (5), 2014)

3D Hand Pose Detection in Egocentric RGB-D Images. - Grégory Rogez; Maryam Khademi; James Steven Supancic III; J. M. M. Montiel; Deva Ramanan (ECCV Workshops (1), 2014)

AutoCaption: Automatic caption generation for personal photos. - Krishnan Ramnath; Simon Baker; Lucy Vanderwende; Motaz Ahmad El-Saban; Sudipta N. Sinha; Anitha Kannan; Noran Hassan; Michel Galley; Yi Yang 007; Deva Ramanan; Alessandro Bergamo; Lorenzo Torresani (WACV, 2014)

Microsoft COCO: Common Objects in Context. - Tsung-Yi Lin; Michael Maire; Serge J. Belongie; Lubomir D. Bourdev; Ross B. Girshick; James Hays; Pietro Perona; Deva Ramanan; Piotr Dollár; C. Lawrence Zitnick (CoRR, 2014)

Egocentric Pose Recognition in Four Lines of Code. - Grégory Rogez; James Steven Supancic III; Deva Ramanan (CoRR, 2014)

Scheduling sensors for monitoring sentient spaces using an approximate POMDP policy. - Ronen Vaisenberg; Alessio Della Motta; Sharad Mehrotra; Deva Ramanan (Pervasive Mob. Comput., 2014)

Articulated pose estimation with tiny synthetic videos. - Dennis Park; Deva Ramanan (CVPR Workshops, 2015)

First-person pose recognition using egocentric workspaces. - Grégory Rogez; James Steven Supancic III; Deva Ramanan (CVPR, 2015)

Look and Think Twice: Capturing Top-Down Visual Attention with Feedback Convolutional Neural Networks. - Chunshui Cao; Xianming Liu; Yi Yang 007; Yinan Yu; Jiang Wang 001; Zilei Wang; Yongzhen Huang; Liang Wang 001; Chang Huang; Wei Xu 017; Deva Ramanan; Thomas S. Huang (ICCV, 2015)

Understanding Everyday Hands in Action from RGB-D Images. - Grégory Rogez; James Steven Supancic III; Deva Ramanan (ICCV, 2015)

Depth-Based Hand Pose Estimation: Data, Methods, and Challenges. - James Steven Supancic III; Grégory Rogez; Yi Yang 007; Jamie Shotton; Deva Ramanan (ICCV, 2015)

Multi-scale Recognition with DAG-CNNs. - Songfan Yang; Deva Ramanan (ICCV, 2015)

Bottom-up and top-down reasoning with convolutional latent-variable models. - Peiyun Hu; Deva Ramanan (CoRR, 2015)

Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussians. - Peiyun Hu; Deva Ramanan (CVPR, 2016)

Categorizing cubes: Revisiting pose normalization. - Mohsen Hejrati; Deva Ramanan (WACV, 2016)

PixelNet: Towards a General Pixel-level Architecture. - Aayush Bansal; Xinlei Chen; Bryan C. Russell; Abhinav Gupta 001; Deva Ramanan (CoRR, 2016)

Tinkering Under the Hood: Interactive Zero-Shot Learning with Net Surgery. - Vivek Krishnan; Deva Ramanan (CoRR, 2016)

The Open World of Micro-Videos. - Phuc Xuan Nguyen; Grégory Rogez; Charless C. Fowlkes; Deva Ramanan (CoRR, 2016)

Guest Editorial: Video Recognition. - Ivan Laptev; Deva Ramanan; Josef Sivic (Int. J. Comput. Vis., 2016)

Do We Need More Training Data? - Xiangxin Zhu; Carl Vondrick; Charless C. Fowlkes; Deva Ramanan (Int. J. Comput. Vis., 2016)

Query-Driven Approach to Face Clustering and Tagging. - Liyan Zhang 001; Xikui Wang; Dmitri V. Kalashnikov; Sharad Mehrotra; Deva Ramanan (IEEE Trans. Image Process., 2016)

Fine-Grained Forensic Matching. - Bailey Kong; James Steven Supancic III; Deva Ramanan; Charless C. Fowlkes (BMVC, 2017)

3D Human Pose Estimation = 2D Pose Estimation + Matching. - Ching-Hang Chen; Deva Ramanan (CVPR, 2017)

Predictive-Corrective Networks for Action Detection. - Achal Dave; Olga Russakovsky; Deva Ramanan (CVPR, 2017)

ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification. - Rohit Girdhar; Deva Ramanan; Abhinav Gupta 001; Josef Sivic; Bryan C. Russell (CVPR, 2017)

Finding Tiny Faces. - Peiyun Hu; Deva Ramanan (CVPR, 2017)

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters. - Shiyu Huang 001; Deva Ramanan (CVPR, 2017)

Growing a Brain: Fine-Tuning by Increasing Model Capacity. - Yu-Xiong Wang; Deva Ramanan; Martial Hebert (CVPR, 2017)

Unconstrained Face Detection and Open-Set Face Recognition Challenge. - Manuel Günther; Peiyun Hu; Christian Herrmann 001; Chi-Ho Chan; Min Jiang 003; Shufan Yang; Akshay Raj Dhamija; Deva Ramanan; Jürgen Beyerer; Josef Kittler; Mohamad Al Jazaery; Mohammad Iqbal Nouyed; et al. (IJCB, 2017)

Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. - Hamed Kiani Galoogahi; Ashton Fagg; Chen Huang 001; Deva Ramanan; Simon Lucey (ICCV, 2017)

Learning Policies for Adaptive Tracking with Deep Feature Cascades. - Chen Huang 001; Simon Lucey; Deva Ramanan (ICCV, 2017)

Tracking as Online Decision-Making: Learning a Policy from Streaming Videos with Reinforcement Learning. - James Steven Supancic III; Deva Ramanan (ICCV, 2017)

Attentional Pooling for Action Recognition. - Rohit Girdhar; Deva Ramanan (NIPS, 2017)

Learning to Model the Tail. - Yu-Xiong Wang; Deva Ramanan; Martial Hebert (NIPS, 2017)

PixelNet: Representation of the pixels, by the pixels, and for the pixels. - Aayush Bansal; Xinlei Chen; Bryan C. Russell; Abhinav Gupta 001; Deva Ramanan (CoRR, 2017)

Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters. - Shiyu Huang 001; Deva Ramanan (CoRR, 2017)

Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset. - Zachary Pezzementi; Trenton Tabor; Peiyun Hu; Jonathan K. Chang; Deva Ramanan; Carl Wellington; Benzun P. Wisely Babu; Herman Herman (CoRR, 2017)

Unconstrained Face Detection and Open-Set Face Recognition Challenge. - Manuel Günther; Peiyun Hu; Christian Herrmann 001; Chi-Ho Chan; Min Jiang 003; Shufan Yang; Akshay Raj Dhamija; Deva Ramanan; Jürgen Beyerer; Josef Kittler; Mohamad Al Jazaery; Mohammad Iqbal Nouyed; et al. (CoRR, 2017)

Brute-Force Facial Landmark Analysis With a 140, 000-Way Classifier. - Mengtian Li; László A. Jeni; Deva Ramanan (AAAI, 2018)

Recycle-GAN: Unsupervised Video Retargeting. - Aayush Bansal; Shugao Ma; Deva Ramanan; Yaser Sheikh (ECCV (5), 2018)

Few-Shot Human Motion Prediction via Meta-learning. - Liang-Yan Gui; Yu-Xiong Wang; Deva Ramanan; José M. F. Moura (ECCV (8), 2018)

PixelNN: Example-based Image Synthesis. - Aayush Bansal; Yaser Sheikh; Deva Ramanan (ICLR (Poster), 2018)

Active Testing: An Efficient and Robust Framework for Estimating Accuracy. - Phuc Xuan Nguyen; Deva Ramanan; Charless C. Fowlkes (ICML, 2018)

Learning Generative Models of Tissue Organization with Supervised GANs. - Ligong Han; Robert F. Murphy; Deva Ramanan (WACV, 2018)

Ensemble Knowledge Transfer for Semantic Segmentation. - Ishan Nigam; Chen Huang 001; Deva Ramanan (WACV, 2018)

The More You Look, the More You See: Towards General Object Understanding Through Recursive Refinement. - Jingyan Wang 001; Olga Russakovsky; Deva Ramanan (WACV, 2018)

Depth-Based Hand Pose Estimation: Methods, Data, and Challenges. - James Steven Supancic III; Grégory Rogez; Yi Yang 007; Jamie Shotton; Deva Ramanan (Int. J. Comput. Vis., 2018)

Comparing apples and oranges: Off-road pedestrian detection on the National Robotics Engineering Center agricultural person-detection dataset. - Zachary Pezzementi; Trenton Tabor; Peiyun Hu; Jonathan K. Chang; Deva Ramanan; Carl Wellington; Benzun P. Wisely Babu; Herman Herman (J. Field Robotics, 2018)

Shapes and Context: In-The-Wild Image Synthesis & Manipulation. - Aayush Bansal; Yaser Sheikh; Deva Ramanan (CVPR, 2019)

Argoverse: 3D Tracking and Forecasting With Rich Maps. - Ming-Fang Chang; John Lambert; Patsorn Sangkloy; Jagjeet Singh; Slawomir Bak; Andrew Hartnett; De Wang; Peter Carr 001; Simon Lucey; Deva Ramanan; James Hays (CVPR, 2019)

Hierarchical Deep Stereo Matching on High-Resolution Images. - Gengshan Yang; Joshua Manela; Michael Happold; Deva Ramanan (CVPR, 2019)

DistInit: Learning Video Representations Without a Single Labeled Video. - Rohit Girdhar; Du Tran; Lorenzo Torresani; Deva Ramanan (ICCV, 2019)

Online Model Distillation for Efficient Video Inference. - Ravi Teja Mullapudi; Steven Chen; Keyi Zhang; Deva Ramanan; Kayvon Fatahalian (ICCV, 2019)

Weakly-Supervised Action Localization With Background Modeling. - Phuc Xuan Nguyen; Deva Ramanan; Charless C. Fowlkes (ICCV, 2019)

Towards Latent Attribute Discovery From Triplet Similarities. - Ishan Nigam; Pavel Tokmakov; Deva Ramanan (ICCV, 2019)

Meta-Learning to Detect Rare Objects. - Yu-Xiong Wang; Deva Ramanan; Martial Hebert (ICCV, 2019)

Towards Segmenting Anything That Moves. - Achal Dave; Pavel Tokmakov; Deva Ramanan (ICCV Workshops, 2019)

Are we Asking the Right Questions in MovieQA? - Bhavan Jasani; Rohit Girdhar; Deva Ramanan (ICCV Workshops, 2019)

Recognizing Tiny Faces. - Siva Chaitanya Mynepalli; Peiyun Hu; Deva Ramanan (ICCV Workshops, 2019)

Active Learning with Partial Feedback. - Peiyun Hu; Zachary C. Lipton; Anima Anandkumar; Deva Ramanan (ICLR (Poster), 2019)

Inferring Distributions Over Depth from a Single Image. - Gengshan Yang; Peiyun Hu; Deva Ramanan (IROS, 2019)

Volumetric Correspondence Networks for Optical Flow. - Gengshan Yang; Deva Ramanan (NeurIPS, 2019)

Photo-Sketching: Inferring Contour Drawings From Images. - Mengtian Li; Zhe Lin 001; Radomír Mech; Ersin Yumer; Deva Ramanan (WACV, 2019)

Towards Segmenting Everything That Moves. - Achal Dave; Pavel Tokmakov; Deva Ramanan (CoRR, 2019)

A systematic framework for natural perturbations from videos. - Vaishaal Shankar; Achal Dave; Rebecca Roelofs; Deva Ramanan; Benjamin Recht; Ludwig Schmidt (CoRR, 2019)

CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning. - Rohit Girdhar; Deva Ramanan (CoRR, 2019)

Learning to Track Any Object. - Achal Dave; Pavel Tokmakov; Cordelia Schmid; Deva Ramanan (CoRR, 2019)

Cross-Domain Image Matching with Deep Feature Maps. - Bailey Kong; James Steven Supancic III; Deva Ramanan; Charless C. Fowlkes (Int. J. Comput. Vis., 2019)

4D Visualization of Dynamic Events From Unconstrained Multi-View Videos. - Aayush Bansal; Minh Vo; Yaser Sheikh; Deva Ramanan; Srinivasa G. Narasimhan (CVPR, 2020)

What You See is What You Get: Exploiting Visibility for 3D Object Detection. - Peiyun Hu; Jason Ziglar; David Held; Deva Ramanan (CVPR, 2020)

Upgrading Optical Flow to 3D Scene Flow Through Optical Expansion. - Gengshan Yang; Deva Ramanan (CVPR, 2020)

TAO: A Large-Scale Benchmark for Tracking Any Object. - Achal Dave; Tarasha Khurana; Pavel Tokmakov; Cordelia Schmid; Deva Ramanan (ECCV (5), 2020)

Towards Streaming Perception. - Mengtian Li; Yu-Xiong Wang; Deva Ramanan (ECCV (2), 2020)

Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild. - Jason Y. Zhang 001; Sam Pepose; Hanbyul Joo; Deva Ramanan; Jitendra Malik; Angjoo Kanazawa (ECCV (12), 2020)

CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning. - Rohit Girdhar; Deva Ramanan (ICLR, 2020)

MetaPix: Few-Shot Video Retargeting. - Jessica Lee; Deva Ramanan; Rohit Girdhar (ICLR, 2020)

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints. - Mengtian Li; Ersin Yumer; Deva Ramanan (ICLR, 2020)

Learning to Move with Affordance Maps. - William Qi; Ravi Teja Mullapudi; Saurabh Gupta 001; Deva Ramanan (ICLR, 2020)

Unsupervised Any-to-Many Audiovisual Synthesis via Exemplar Autoencoders. - Kangle Deng; Aayush Bansal; Deva Ramanan (CoRR, 2020)

Towards Streaming Image Understanding. - Mengtian Li; Yu-Xiong Wang; Deva Ramanan (CoRR, 2020)

What-If Motion Prediction for Autonomous Driving. - Siddhesh Khandelwal; William Qi; Jagjeet Singh; Andrew Hartnett; Deva Ramanan (CoRR, 2020)

Learning to Optimally Segment Point Clouds. - Peiyun Hu; David Held; Deva Ramanan (IEEE Robotics Autom. Lett., 2020)

Safe Local Motion Planning With Self-Supervised Freespace Forecasting. - Peiyun Hu; Aaron Huang; John M. Dolan; David Held; Deva Ramanan (CVPR, 2021)

Background Splitting: Finding Rare Classes in a Sea of Background. - Ravi Teja Mullapudi; Fait Poms; William R. Mark; Deva Ramanan; Kayvon Fatahalian (CVPR, 2021)

Learning To Segment Rigid Motions From Two Frames. - Gengshan Yang; Deva Ramanan (CVPR, 2021)

LASR: Learning Articulated Shape Reconstruction From a Monocular Video. - Gengshan Yang; Deqing Sun; Varun Jampani; Daniel Vlasic; Forrester Cole; Huiwen Chang; Deva Ramanan; William T. Freeman; Ce Liu 001 (CVPR, 2021)

Detecting Invisible People. - Tarasha Khurana; Achal Dave; Deva Ramanan (ICCV, 2021)

Learning Rare Category Classifiers on a Tight Labeling Budget. - Ravi Teja Mullapudi; Fait Poms; William R. Mark; Deva Ramanan; Kayvon Fatahalian (ICCV, 2021)

Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories. - Fait Poms; Vishnu Sarukkai; Ravi Teja Mullapudi; Nimit Sharad Sohoni; William R. Mark; Deva Ramanan; Kayvon Fatahalian (ICCV, 2021)

Do Image Classifiers Generalize Across Time? - Vaishaal Shankar; Achal Dave; Rebecca Roelofs; Deva Ramanan; Benjamin Recht; Ludwig Schmidt (ICCV, 2021)

FOVEA: Foveated Image Magnification for Autonomous Navigation. - Chittesh Thavamani; Mengtian Li; Nicolas Cebron; Deva Ramanan (ICCV, 2021)

Unsupervised Audiovisual Synthesis via Exemplar Autoencoders. - Kangle Deng; Aayush Bansal; Deva Ramanan (ICLR, 2021)

The CLEAR Benchmark: Continual LEArning on Real-World Imagery. - Zhiqiu Lin; Jia Shi; Deepak Pathak; Deva Ramanan (NeurIPS Datasets and Benchmarks, 2021)

Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting. - Benjamin Wilson; William Qi; Tanmay Agarwal; John Lambert; Jagjeet Singh; Siddhesh Khandelwal; Bowen Pan; Ratnesh Kumar; Andrew Hartnett; Jhony Kaesemodel Pontes; Deva Ramanan; Peter Carr 001; et al. (NeurIPS Datasets and Benchmarks, 2021)

ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction. - Gengshan Yang; Deqing Sun; Varun Jampani; Daniel Vlasic; Forrester Cole; Ce Liu 001; Deva Ramanan (NeurIPS, 2021)

NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild. - Jason Y. Zhang 001; Gengshan Yang; Shubham Tulsiani; Deva Ramanan (NeurIPS, 2021)

Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details. - Achal Dave; Piotr Dollár; Deva Ramanan; Alexander Kirillov; Ross B. Girshick (CoRR, 2021)

Video Exploration via Video-Specific Autoencoders. - Kevin Wang; Deva Ramanan; Aayush Bansal (CoRR, 2021)

Multimodal Object Detection via Bayesian Fusion. - Yi-Ting Chen; Jinghao Shi; Christoph Mertz; Shu Kong; Deva Ramanan (CoRR, 2021)

Streaming Self-Training via Domain-Agnostic Unlabeled Images. - Zhiqiu Lin; Deva Ramanan; Aayush Bansal (CoRR, 2021)

Towards Long-Tailed 3D Detection. - Neehar Peri; Achal Dave; Deva Ramanan; Shu Kong (CoRL, 2022)

Long- Tailed Recognition via Weight Balancing. - Shaden Alshammari; Yu-Xiong Wang; Deva Ramanan; Shu Kong (CVPR, 2022)

HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images. - Ali Athar; Jonathon Luiten; Alexander Hermans; Deva Ramanan; Bastian Leibe (CVPR, 2022)

Depth-supervised NeRF: Fewer Views and Faster Training for Free. - Kangle Deng; Andrew Liu 001; Jun-Yan Zhu; Deva Ramanan (CVPR, 2022)

Opening up Open World Tracking. - Yang Liu; Idil Esen Zulfikar; Jonathon Luiten; Achal Dave; Deva Ramanan; Bastian Leibe; Aljosa Osep; Laura Leal-Taixé (CVPR, 2022)

Forecasting from LiDAR via Future Object Detection. - Neehar Peri; Jonathon Luiten; Mengtian Li; Aljosa Osep; Laura Leal-Taixé; Deva Ramanan (CVPR, 2022)

Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly- Throughs. - Haithem Turki; Deva Ramanan; Mahadev Satyanarayanan (CVPR, 2022)

BANMo: Building Animatable 3D Neural Models from Many Casual Videos. - Gengshan Yang; Minh Vo; Natalia Neverova; Deva Ramanan; Andrea Vedaldi; Hanbyul Joo (CVPR, 2022)

Multimodal Object Detection via Probabilistic Ensembling. - Yi-Ting Chen; Jinghao Shi; Zelin Ye; Christoph Mertz; Deva Ramanan; Shu Kong (ECCV (9), 2022)

Differentiable Raycasting for Self-Supervised Occupancy Forecasting. - Tarasha Khurana; Peiyun Hu; Achal Dave; Jason Ziglar; David Held; Deva Ramanan (ECCV (38), 2022)

RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wild. - Jason Y. Zhang 001; Deva Ramanan; Shubham Tulsiani (ECCV (31), 2022)

Learning to Discover and Detect Objects. - Vladimir Fomenko; Ismail Elezi; Deva Ramanan; Laura Leal-Taixé; Aljosa Osep (NeurIPS, 2022)

Continual Learning with Evolving Class Ontologies. - Zhiqiu Lin; Deepak Pathak; Yu-Xiong Wang; Deva Ramanan; Shu Kong (NeurIPS, 2022)

Robust Modeling and Controls for Racing on the Edge. - Joshua Spisak; Andrew Saba; Nayana Suvarna; Brian Mao; Chuan Tian Zhang; Chris Chang; Sebastian A. Scherer; Deva Ramanan (CoRR, 2022)

Differentiable Soft-Masked Attention. - Ali Athar; Jonathon Luiten; Alexander Hermans; Deva Ramanan; Bastian Leibe (CoRR, 2022)

Learning Generic Lung Ultrasound Biomarkers for Decoupling Feature Extraction from Downstream Tasks. - Gautam Rajendrakumar Gare; Tom Fox; Peter Lowery; Kevin Zamora; Hai V. Tran; Laura Hutchins; David Montgomery; Amita Krishnan; Deva Kannan Ramanan; Ricardo Luis Rodriguez; Bennett P. deBoisblanc; John Michael Galeotti (CoRR, 2022)

Learning with an Evolving Class Ontology. - Zhiqiu Lin; Deepak Pathak; Yu-Xiong Wang; Deva Ramanan; Shu Kong (CoRR, 2022)

TarViS: A Unified Approach for Target-Based Video Segmentation. - Ali Athar; Alexander Hermans; Jonathon Luiten; Deva Ramanan; Bastian Leibe (CVPR, 2023)

3D-aware Conditional Image Synthesis. - Kangle Deng; Gengshan Yang; Deva Ramanan; Jun-Yan Zhu (CVPR, 2023)

Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting. - Tarasha Khurana; Peiyun Hu; David Held; Deva Ramanan (CVPR, 2023)

Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models. - Zhiqiu Lin; Samuel Yu; Zhiyi Kuang 002; Deepak Pathak; Deva Ramanan (CVPR, 2023)

Soft Augmentation for Image Classification. - Yang Liu; Shen Yan; Laura Leal-Taixé; James Hays; Deva Ramanan (CVPR, 2023)

WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models. - Aboli Marathe; Deva Ramanan; Rahee Walambe; Ketan Kotecha (CVPR Workshops, 2023)

Distilling Neural Fields for Real-Time Articulated Shape Reconstruction. - Jeff Tan; Gengshan Yang; Deva Ramanan (CVPR, 2023)

Learning to Zoom and Unzoom. - Chittesh Thavamani; Mengtian Li; Francesco Ferroni; Deva Ramanan (CVPR, 2023)

SUDS: Scalable Urban Dynamic Scenes. - Haithem Turki; Jason Y. Zhang 001; Francesco Ferroni; Deva Ramanan (CVPR, 2023)

Pix2Map: Cross-Modal Retrieval for Inferring Street Maps from Images. - Xindi Wu; KwunFung Lau; Francesco Ferroni; Aljosa Osep; Deva Ramanan (CVPR, 2023)

Reconstructing Animatable Categories from Videos. - Gengshan Yang; Chaoyang Wang 001; N. Dinesh Reddy; Deva Ramanan (CVPR, 2023)

Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis. - Chonghyuk Song; Gengshan Yang; Kangle Deng; Jun-Yan Zhu; Deva Ramanan (ICCV, 2023)

Joint Metrics Matter: A Better Standard for Trajectory Forecasting. - Erica Weng; Hana Hoshino; Deva Ramanan; Kris Kitani (ICCV, 2023)

PPR: Physically Plausible Reconstruction from Monocular Videos. - Gengshan Yang; Shuo Yang; John Z. Zhang; Zachary Manchester; Deva Ramanan (ICCV, 2023)

An Empirical Analysis of Range for 3D Object Detection. - Neehar Peri; Mengtian Li; Benjamin Wilson; Yu-Xiong Wang; James Hays; Deva Ramanan (ICCV (Workshops), 2023)

Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation. - Shengcao Cao; Mengtian Li; James Hays; Deva Ramanan; Yu-Xiong Wang; Liangyan Gui (ICML, 2023)

Lidar Panoptic Segmentation and Tracking without Bells and Whistles. - Abhinav Agarwalla; Xuhua Huang; Jason Ziglar; Francesco Ferroni; Laura Leal-Taixé; James Hays; Aljosa Osep; Deva Ramanan (IROS, 2023)

Streaming Motion Forecasting for Autonomous Driving. - Ziqi Pang; Deva Ramanan; Mengtian Li; Yu-Xiong Wang (IROS, 2023)

Low-Bandwidth Self-Improving Transmission of Rare Training Data. - Shilpa Anna George; Haithem Turki; Ziqiang Feng; Deva Ramanan; Padmanabhan Pillai; Mahadev Satyanarayanan (MobiCom, 2023)

Edge-based Privacy-Sensitive Live Learning for Discovery of Training Data. - Shilpa Anna George; Haithem Turki; Ziqiang Feng; Deva Ramanan; Padmanabhan Pillai; Mahadev Satyanarayanan (NetAISys@MobiSys, 2023)

PyNeRF: Pyramidal Neural Radiance Fields. - Haithem Turki; Michael Zollhöfer; Christian Richardt; Deva Ramanan (NeurIPS, 2023)

BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video. - Ali Athar; Jonathon Luiten; Paul Voigtlaender; Tarasha Khurana; Achal Dave; Bastian Leibe; Deva Ramanan (WACV, 2023)

Far3Det: Towards Far-Field 3D Detection. - Shubham Gupta; Jeet Kanjani; Mengtian Li; Francesco Ferroni; James Hays; Deva Ramanan; Shu Kong (WACV, 2023)

Re-Evaluating LiDAR Scene Flow for Autonomous Driving. - Nathaniel Chodosh; Deva Ramanan; Simon Lucey (CoRR, 2023)

SLoMo: A General System for Legged Robot Motion Imitation from Casual Videos. - John Z. Zhang; Shuo Yang; Gengshan Yang; Arun L. Bishop; Deva Ramanan; Zachary Manchester (CoRR, 2023)

ZeroFlow: Fast Zero Label Scene Flow via Distillation. - Kyle Vedder; Neehar Peri; Nathaniel Chodosh; Ishan Khatri; Eric Eaton; Dinesh Jayaraman; Yang Liu; Deva Ramanan; James Hays (CoRR, 2023)

VisualGPTScore: Visio-Linguistic Reasoning with Multimodal Generative Pre-Training Scores. - Zhiqiu Lin; Xinyue Chen; Deepak Pathak; Pengchuan Zhang; Deva Ramanan (CoRR, 2023)

Thinking Like an Annotator: Generation of Dataset Labeling Instructions. - Nadine Chang; Francesco Ferroni; Michael J. Tarr; Martial Hebert; Deva Ramanan (CoRR, 2023)

Evaluating a VR System for Collecting Safety-Critical Vehicle-Pedestrian Interactions. - Erica Weng; Kenta Mukoya; Deva Ramanan; Kris Kitani (CoRR, 2023)

Long-Tailed 3D Detection via 2D Late Fusion. - Yechi Ma; Neehar Peri; Shuoquan Wei; Wei Hua; Deva Ramanan; Yanan Li; Shu Kong (CoRR, 2023)

Tracking Any Object Amodally. - Cheng-Yen Hsieh; Tarasha Khurana; Achal Dave; Deva Ramanan (CoRR, 2023)

SLoMo: A General System for Legged Robot Motion Imitation From Casual Videos. - John Z. Zhang; Shuo Yang; Gengshan Yang; Arun L. Bishop; Swaminathan Gurumurthy; Deva Ramanan; Zachary Manchester (IEEE Robotics Autom. Lett., 2023)

RelPose++: Recovering 6D Poses from Sparse-view Observations. - Amy Lin; Jason Y. Zhang 001; Deva Ramanan; Shubham Tulsiani (3DV, 2024)

Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis. - Jonathon Luiten; Georgios Kopanas; Bastian Leibe; Deva Ramanan (3DV, 2024)

Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection. - Mehar Khurana; Neehar Peri; James Hays; Deva Ramanan (CoRL, 2024)

SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM. - Nikhil Varma Keetha; Jay Karhade; Krishna Murthy Jatavallabhula; Gengshan Yang; Sebastian A. Scherer; Deva Ramanan; Jonathon Luiten (CVPR, 2024)

Evaluating and Improving Compositional Text-to-Visual Generation. - Baiqi Li; Zhiqiu Lin; Deepak Pathak; Jiayao Li; Yixin Fei; Kewen Wu 005; Xide Xia; Pengchuan Zhang; Graham Neubig; Deva Ramanan (CVPR Workshops, 2024)

Language Models as Black-Box Optimizers for Vision-Language Models. - Shihong Liu; Samuel Yu; Zhiqiu Lin; Deepak Pathak; Deva Ramanan (CVPR, 2024)

The Neglected Tails in Vision-Language Models. - Shubham Parashar; Zhiqiu Lin; Tian Liu 006; Xiangjue Dong; Yanan Li; Deva Ramanan; James Caverlee; Shu Kong (CVPR, 2024)

HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces. - Haithem Turki; Vasu Agrawal; Samuel Rota Bulò; Lorenzo Porzi; Peter Kontschieder; Deva Ramanan; Michael Zollhöfer; Christian Richardt (CVPR, 2024)

FlashTex: Fast Relightable Mesh Texturing with LightControlNet. - Kangle Deng; Timothy Omernick; Alexander Weiss; Deva Ramanan; Jun-Yan Zhu; Tinghui Zhou; Maneesh Agrawala (ECCV (27), 2024)

I Can't Believe It's Not Scene Flow! - Ishan Khatri; Kyle Vedder; Neehar Peri; Deva Ramanan; James Hays (ECCV (18), 2024)

Evaluating Text-to-Visual Generation with Image-to-Text Generation. - Zhiqiu Lin; Deepak Pathak; Baiqi Li; Jiayao Li; Xide Xia; Graham Neubig; Pengchuan Zhang; Deva Ramanan (ECCV (9), 2024)

Better Call SAL: Towards Learning to Segment Anything in Lidar. - Aljosa Osep; Tim Meinhardt; Francesco Ferroni; Neehar Peri; Deva Ramanan; Laura Leal-Taixé (ECCV (39), 2024)

Cameras as Rays: Pose Estimation via Ray Diffusion. - Jason Y. Zhang 001; Amy Lin; Moneish Kumar; Tzu-Hsuan Yang; Deva Ramanan; Shubham Tulsiani (ICLR, 2024)

ZeroFlow: Scalable Scene Flow via Distillation. - Kyle Vedder; Neehar Peri; Nathaniel Chodosh; Ishan Khatri; Eric Eaton; Dinesh Jayaraman; Yang Liu; Deva Ramanan; James Hays (ICLR, 2024)

Revisiting the Role of Language Priors in Vision-Language Models. - Zhiqiu Lin; Xinyue Chen; Deepak Pathak; Pengchuan Zhang; Deva Ramanan (ICML, 2024)

NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples. - Baiqi Li; Zhiqiu Lin; Wenxuan Peng; Jean de Dieu Nyandwi; Daniel Jiang; Zixian Ma; Simran Khanuja; Ranjay Krishna; Graham Neubig; Deva Ramanan (NeurIPS, 2024)

Revisiting Few-Shot Object Detection with Vision-Language Models. - Anish Madan; Neehar Peri; Shu Kong; Deva Ramanan (NeurIPS, 2024)

Re-Evaluating LiDAR Scene Flow. - Nathaniel Chodosh; Deva Ramanan; Simon Lucey (WACV, 2024)

Improving Model's Interpretability and Reliability using Biomarkers. - Gautam Rajendrakumar Gare; Tom Fox; Beam Chansangavej; Amita Krishnan; Ricardo Luis Rodriguez; Bennett P. deBoisblanc; Deva Kannan Ramanan; John Michael Galeotti (CoRR, 2024)

Predicting Long-horizon Futures by Conditioning on Geometry and Time. - Tarasha Khurana; Deva Ramanan (CoRR, 2024)

Neural Representations of Dynamic Visual Stimuli. - Jacob Yeung; Andrew F. Luo; Gabriel Sarch; Margaret M. Henderson; Deva Ramanan; Michael J. Tarr (CoRR, 2024)

Shelf-Supervised Multi-Modal Pre-Training for 3D Object Detection. - Mehar Khurana; Neehar Peri; Deva Ramanan; James Hays (CoRR, 2024)

Planning with Adaptive World Models for Autonomous Driving. - Arun Balajee Vasudevan; Neehar Peri; Jeff Schneider; Deva Ramanan (CoRR, 2024)

GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation. - Baiqi Li; Zhiqiu Lin; Deepak Pathak; Jiayao Li; Yixin Fei; Kewen Wu 005; Tiffany Ling; Xide Xia; Pengchuan Zhang; Graham Neubig; Deva Ramanan (CoRR, 2024)

Simultaneous Map and Object Reconstruction. - Nathaniel Chodosh; Anish Madan; Deva Ramanan; Simon Lucey (CoRR, 2024)

LEARNER: Learning Granular Labels from Coarse Labels using Contrastive Learning. - Gautam Rajendrakumar Gare; Jana Armouti; Nikhil Madaan; Rohan Panda; Tom Fox; Laura Hutchins; Amita Krishnan; Ricardo Luis Rodriguez; Bennett P. deBoisblanc; Deva Ramanan; John M. Galeotti (CoRR, 2024)

Sparse Attention Vectors: Generative Multimodal Model Features Are Discriminative Vision-Language Classifiers. - Chancharik Mitra; Brandon Huang; Tianning Chai; Zhiqiu Lin; Assaf Arbelle; Rogério Feris; Leonid Karlinsky; Trevor Darrell; Deva Ramanan; Roei Herzig (CoRR, 2024)

Fast and Modular Autonomy Software for Autonomous Racing Vehicles. - Andrew Saba; Aderotimi Adetunji; Adam Johnson; Aadi Kothari; Matthew Sivaprakasam; Joshua Spisak; Prem Bharatia; Arjun Chauhan; Brendan Duff Jr.; Noah Gasparro; Charles King; Ryan Larkin; et al. (Field Robotics, 2024)

SMORE: Simultaneous Map and Object REconstruction. - Nathaniel Chodosh; Anish Madan; Simon Lucey; Deva Ramanan (3DV, 2025)

DynOMo: Online Point Tracking by Dynamic Online Monocular Gaussian Reconstruction. - Jenny Seidenschwarz; Qunjie Zhou; Bardienus Pieter Duisterhof; Deva Ramanan; Laura Leal-Taixé (3DV, 2025)

DressRecon: Freeform 4D Human Reconstruction from Monocular Video. - Jeff Tan; Donglai Xiang; Shubham Tulsiani; Deva Ramanan; Gengshan Yang (3DV, 2025)

InstructPart: Task-Oriented Part Segmentation with Instruction Reasoning. - Zifu Wan; Yaqi Xie 001; Ce Zhang 009; Zhiqiu Lin; Zihan Wang; Simon Stepputtis; Deva Ramanan; Katia P. Sycara (ACL (1), 2025)

Using Diffusion Priors for Video Amodal Segmentation. - Kaihua Chen; Deva Ramanan; Tarasha Khurana (CVPR, 2025)

AerialMegaDepth: Learning Aerial-Ground Reconstruction and View Synthesis. - Khiem Vuong; Anurag Ghosh; Deva Ramanan; Srinivasa Narasimhan; Shubham Tulsiani (CVPR, 2025)

Reanimating Images using Neural Representations of Dynamic Stimuli. - Jacob Yeung; Andrew F. Luo; Gabriel Sarch; Margaret M. Henderson; Deva Ramanan; Michael J. Tarr (CVPR, 2025)

DiffusionSfM: Predicting Structure and Motion via Ray Origin and Endpoint Diffusion. - Qitao Zhao; Amy Lin; Jeff Tan; Jason Y. Zhang 001; Deva Ramanan; Shubham Tulsiani (CVPR, 2025)

Self-Correcting Decoding with Generative Feedback for Mitigating Hallucinations in Large Vision-Language Models. - Ce Zhang 009; Zifu Wan; Zhehan Kan; Martin Q. Ma; Simon Stepputtis; Deva Ramanan; Russ Salakhutdinov; Louis-Philippe Morency; Katia P. Sycara; Yaqi Xie 001 (ICLR, 2025)

Neural Eulerian Scene Flow Fields. - Kyle Vedder; Neehar Peri; Ishan Khatri; Siyi Li; Eric Eaton; Mehmet Kemal Kocamaz; Yue Wang; Zhiding Yu; Deva Ramanan; Joachim Pehserl (ICLR, 2025)

Accenture-NVS1: A Novel View Synthesis Dataset. - Thomas Sugg; Kyle O'Brien; Lekh Poudel; Alex Dumouchelle; Michelle Jou; Marc Bosch; Deva Ramanan; Srinivasa Narasimhan; Shubham Tulsiani (CoRR, 2025)

Lidar Panoptic Segmentation in an Open World. - Anirudh Srinivasan Chakravarthy; Meghana Reddy Ganesina; Peiyun Hu; Laura Leal-Taixé; Shu Kong; Deva Ramanan; Aljosa Osep (Int. J. Comput. Vis., 2025)

Efficient Autoregressive Shape Generation via Octree-Based Adaptive Tokenization. - Kangle Deng; Hsueh-Ti Derek Liu; Yiheng Zhu; Xiaoxia Sun; Chong Shang; Kiran Bhat; Deva Ramanan; Jun-Yan Zhu; Maneesh Agrawala; Tinghui Zhou (CoRR, 2025)

AerialMegaDepth: Learning Aerial-Ground Reconstruction and View Synthesis. - Khiem Vuong; Anurag Ghosh; Deva Ramanan; Srinivasa G. Narasimhan; Shubham Tulsiani (CoRR, 2025)

Towards Understanding Camera Motions in Any Video. - Zhiqiu Lin; Siyuan Cen; Daniel Jiang; Jay Karhade; Hewei Wang 001; Chancharik Mitra; Tiffany Ling; Yuhan Huang; Sifan Liu; Mingyu Chen; Rushikesh Zawar; Xue Bai; et al. (CoRR, 2025)

Generating Physically Stable and Buildable LEGO Designs from Text. - Ava Pun; Kangle Deng; Ruixuan Liu; Deva Ramanan; Changliu Liu; Jun-Yan Zhu (CoRR, 2025)

BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy. - Micah Nye; Ayoub Raji; Andrew Saba; Eidan Erlich; Robert Exley; Aragya Goyal; Alexander Matros; Ritesh Misra; Matthew Sivaprakasam; Marko Bertogna; Deva Ramanan; Sebastian A. Scherer (CoRR, 2025)

Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models. - Peter Robicheaux; Matvei Popov; Anish Madan; Isaac Robinson; Joseph Nelson; Deva Ramanan; Neehar Peri (CoRR, 2025)

RefAV: Towards Planning-Centric Scenario Mining. - Cainan Davidson; Deva Ramanan; Neehar Peri (CoRR, 2025)

OpenGAN: Open-Set Recognition via Open Data Generation. - Shu Kong; Deva Ramanan (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

RaySt3R: Predicting Novel Depth Maps for Zero-Shot Object Completion. - Bardienus Pieter Duisterhof; Jan Oberst; Bowen Wen; Stan Birchfield; Deva Ramanan; Jeffrey Ichnowski (CoRR, 2025)

UFM: A Simple Path towards Unified Dense Correspondence with Flow. - Yuchen Zhang; Nikhil Varma Keetha; Chenwei Lyu; Bhuvan Jhamb; Yutian Chen; Yuheng Qiu; Jay Karhade; Shreyas Jha; Yaoyu Hu; Deva Ramanan; Sebastian A. Scherer; Wenshan Wang (CoRR, 2025)

ONLY: One-Layer Intervention Sufficiently Mitigates Hallucinations in Large Vision-Language Models. - Zifu Wan; Ce Zhang 009; Silong Yong; Martin Q. Ma; Simon Stepputtis; Louis-Philippe Morency; Deva Ramanan; Katia P. Sycara; Yaqi Xie 001 (CoRR, 2025)

Activation Reward Models for Few-Shot Model Alignment. - Tianning Chai; Chancharik Mitra; Brandon Huang; Gautam Rajendrakumar Gare; Zhiqiu Lin; Assaf Arbelle; Leonid Karlinsky; Rogério Feris; Trevor Darrell; Deva Ramanan; Roei Herzig (CoRR, 2025)

Reconstruct, Inpaint, Finetune: Dynamic Novel-view Synthesis from Monocular Videos. - Kaihua Chen; Tarasha Khurana; Deva Ramanan (CoRR, 2025)

MonoFusion: Sparse-View 4D Reconstruction via Monocular Fusion. - Zihan Wang; Jeff Tan; Tarasha Khurana; Neehar Peri; Deva Ramanan (CoRR, 2025)