Optical Flow Estimation and Segmentation of Multiple Moving Dynamic Textures. - René Vidal; Avinash Ravichandran (CVPR (2), 2005)

Segmenting a beating heart using polysegment and Spatial GPCA. - Avinash Ravichandran; René Vidal; Henry R. Halperin (ISBI, 2006)

Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions. - Rizwan Chaudhry; Avinash Ravichandran; Gregory D. Hager; René Vidal (CVPR, 2009)

View-invariant dynamic texture recognition using a bag of dynamical systems. - Avinash Ravichandran; Rizwan Chaudhry; René Vidal (CVPR, 2009)

A Unified Approach to Segmentation and Categorization of Dynamic Textures. - Avinash Ravichandran; Paolo Favaro; René Vidal (ACCV (1), 2010)

A closed form solution to robust subspace estimation and clustering. - Paolo Favaro; René Vidal; Avinash Ravichandran (CVPR, 2011)

Video Registration Using Dynamic Textures. - Avinash Ravichandran; René Vidal (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Image Priors for Image Deblurring with Uncertain Blur. - Daniele Perrone; Avinash Ravichandran; René Vidal; Paolo Favaro (BMVC, 2012)

Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynamic scenes. - Bijan Afsari; Rizwan Chaudhry; Avinash Ravichandran; René Vidal (CVPR, 2012)

Long-Range Spatio-Temporal Modeling of Video with Application to Fire Detection. - Avinash Ravichandran; Stefano Soatto (ECCV (2), 2012)

SuperFloxels: A Mid-level Representation for Video Sequences. - Avinash Ravichandran; Chaohui Wang; Michalis Raptis; Stefano Soatto (ECCV Workshops (3), 2012)

Semantic Video Segmentation from Occlusion Relations within a Convex Optimization Framework. - Brian Taylor 001; Alper Ayvaci; Avinash Ravichandran; Stefano Soatto (EMMCVPR, 2013)

Categorizing Dynamic Textures Using a Bag of Dynamical Systems. - Avinash Ravichandran; Rizwan Chaudhry; René Vidal (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation. - Vasiliy Karasev; Avinash Ravichandran; Stefano Soatto (CVPR, 2014)

Meta-Learning With Differentiable Convex Optimization. - Kwonjoon Lee; Subhransu Maji; Avinash Ravichandran; Stefano Soatto (CVPR, 2019)

Task2Vec: Task Embedding for Meta-Learning. - Alessandro Achille; Michael Lam; Rahul Tewari; Avinash Ravichandran; Subhransu Maji; Charless C. Fowlkes; Stefano Soatto; Pietro Perona (ICCV, 2019)

Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training. - Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICCV, 2019)

Unbiased Evaluation of Deep Metric Learning Algorithms. - István Fehérvári; Avinash Ravichandran; Srikar Appalaraju (CoRR, 2019)

Incremental Few-Shot Meta-learning via Indirect Discriminant Alignment. - Qing Liu; Orchid Majumder; Alessandro Achille; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ECCV (7), 2020)

A Baseline for Few-Shot Image Classification. - Guneet Singh Dhillon; Pratik Chaudhari; Avinash Ravichandran; Stefano Soatto (ICLR, 2020)

Rethinking the Hyperparameters for Fine-tuning. - Hao Li; Pratik Chaudhari; Hao Yang 043; Michael Lam; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICLR, 2020)

Predicting Training Time Without Training. - Luca Zancato; Alessandro Achille; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (NeurIPS, 2020)

Incremental Learning for Metric-Based Meta-Learners. - Qing Liu; Orchid Majumder; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (CoRR, 2020)

Continual Universal Object Detection. - Xialei Liu; Hao Yang 043; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (CoRR, 2020)

LQF: Linear Quadratic Fine-Tuning. - Alessandro Achille; Aditya Golatkar; Avinash Ravichandran; Marzia Polito; Stefano Soatto (CVPR, 2021)

Exponential Moving Average Normalization for Self-Supervised and Semi-Supervised Learning. - Zhaowei Cai; Avinash Ravichandran; Subhransu Maji; Charless C. Fowlkes; Zhuowen Tu; Stefano Soatto (CVPR, 2021)

Mixed-Privacy Forgetting in Deep Networks. - Aditya Golatkar; Alessandro Achille; Avinash Ravichandran; Marzia Polito; Stefano Soatto (CVPR, 2021)

Estimating informativeness of samples with Smooth Unique Information. - Hrayr Harutyunyan; Alessandro Achille; Giovanni Paolini; Orchid Majumder; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICLR, 2021)

Uniform Sampling over Episode Difficulty. - Sébastien M. R. Arnold; Guneet S. Dhillon; Avinash Ravichandran; Stefano Soatto (NeurIPS, 2021)

Revisiting Contrastive Learning for Few-Shot Classification. - Orchid Majumder; Avinash Ravichandran; Subhransu Maji; Marzia Polito; Rahul Bhotika; Stefano Soatto (CoRR, 2021)

A linearized framework and a new benchmark for model selection for fine-tuning. - Aditya Deshpande; Alessandro Achille; Avinash Ravichandran; Hao Li; Luca Zancato; Charless C. Fowlkes; Rahul Bhotika; Stefano Soatto; Pietro Perona (CoRR, 2021)

Representation Consolidation for Training Expert Students. - Zhizhong Li; Avinash Ravichandran; Charless C. Fowlkes; Marzia Polito; Rahul Bhotika; Stefano Soatto (CoRR, 2021)

Task Adaptive Parameter Sharing for Multi-Task Learning. - Matthew Wallingford; Hao Li; Alessandro Achille; Avinash Ravichandran; Charless C. Fowlkes; Rahul Bhotika; Stefano Soatto (CVPR, 2022)

Class-Incremental Learning with Strong Pre-trained Models. - Tz-Ying Wu; Gurumurthy Swaminathan; Zhizhong Li; Avinash Ravichandran; Nuno Vasconcelos; Rahul Bhotika; Stefano Soatto (CVPR, 2022)

X-DETR: A Versatile Architecture for Instance-wise Vision-Language Tasks. - Zhaowei Cai; Gukyeong Kwon; Avinash Ravichandran; Erhan Bas; Zhuowen Tu; Rahul Bhotika; Stefano Soatto (ECCV (36), 2022)

Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark. - Kibok Lee 003; Hao Yang 043; Satyaki Chakraborty; Zhaowei Cai; Gurumurthy Swaminathan; Avinash Ravichandran; Onkar Dabeer (ECCV (20), 2022)

DIVA: Dataset Derivative of a Learning Task. - Yonatan Dukler; Alessandro Achille; Giovanni Paolini; Avinash Ravichandran; Marzia Polito; Stefano Soatto (ICLR, 2022)

Semi-supervised Vision Transformers at Scale. - Zhaowei Cai; Avinash Ravichandran; Paolo Favaro; Manchen Wang; Davide Modolo; Rahul Bhotika; Zhuowen Tu; Stefano Soatto (NeurIPS, 2022)

ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers. - Achin Jain; Kibok Lee 003; Gurumurthy Swaminathan; Hao Yang 043; Bernt Schiele; Avinash Ravichandran; Onkar Dabeer (CoRR, 2022)

Learning Expressive Prompting With Residuals for Vision Transformers. - Rajshekhar Das; Yonatan Dukler; Avinash Ravichandran; Ashwin Swaminathan (CVPR, 2023)

A Meta-Learning Approach to Predicting Performance and Data Requirements. - Achin Jain; Gurumurthy Swaminathan; Paolo Favaro; Hao Yang 043; Avinash Ravichandran; Hrayr Harutyunyan; Alessandro Achille; Onkar Dabeer; Bernt Schiele; Ashwin Swaminathan; Stefano Soatto (CVPR, 2023)

WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation. - Jongheon Jeong; Yang Zou; Taewan Kim; Dongqing Zhang; Avinash Ravichandran; Onkar Dabeer (CVPR, 2023)

Masked Vision and Language Modeling for Multi-modal Representation Learning. - Gukyeong Kwon; Zhaowei Cai; Avinash Ravichandran; Erhan Bas; Rahul Bhotika; Stefano Soatto (ICLR, 2023)

Your representations are in the network: composable and parallel adaptation for large scale models. - Yonatan Dukler; Alessandro Achille; Hao Yang 043; Varsha Vivek; Luca Zancato; Benjamin Bowman; Avinash Ravichandran; Charless C. Fowlkes; Ashwin Swaminathan; Stefano Soatto (NeurIPS, 2023)

Introspective Cross-Attention Probing for Lightweight Transfer of Pre-trained Models. - Yonatan Dukler; Alessandro Achille; Hao Yang 043; Varsha Vivek; Luca Zancato; Benjamin Bowman; Avinash Ravichandran; Charless C. Fowlkes; Ashwin Swaminathan; Stefano Soatto (CoRR, 2023)

GenMM: Geometrically and Temporally Consistent Multimodal Data Generation for Video and LiDAR. - Bharat Singh; Viveka Kulharia; Luyu Yang; Avinash Ravichandran; Ambrish Tyagi; Ashish Shrivastava 001 (CoRR, 2024)

InVi: Object Insertion In Videos Using Off-the-Shelf Diffusion Models. - Nirat Saini; Navaneeth Bodla; Ashish Shrivastava 001; Avinash Ravichandran; Xiao Zhang; Abhinav Shrivastava; Bharat Singh (CoRR, 2024)

VLM-KD: Knowledge Distillation from VLM for Long-Tail Visual Recognition. - Zaiwei Zhang; Gregory P. Meyer; Zhichao Lu; Ashish Shrivastava 001; Avinash Ravichandran; Eric M. Wolff (CoRR, 2024)

CLAP: Unsupervised 3D Representation Learning for Fusion 3D Perception via Curvature Sampling and Prototype Learning. - Runjian Chen; Hang Zhang; Avinash Ravichandran; Wenqi Shao; Alex Wong 001; Ping Luo 002 (CoRR, 2024)

Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation. - Reza Akbarian Bafghi; Carden Bagwell; Avinash Ravichandran; Ashish Shrivastava; Maziar Raissi (CoRR, 2025)

Training Domain Draft Models for Speculative Decoding: Best Practices and Insights. - Fenglu Hong; Ravi Raju; Jonathan Lingjie Li; Bo Li; Urmish Thakker; Avinash Ravichandran; Swayambhoo Jain; Changran Hu (CoRR, 2025)