Suhas Lohit

According to our database, Suhas Lohit authored at least 36 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups.

Sourya Basu, Suhas Lohit, Matthew Brand

CoRR, 2024

Pixel-Grounded Prototypical Part Networks.

Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection.

Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael Jones

CoRR, 2023

Pixel-Grounded Prototypical Part Networks.

Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael N. Jones, Walter J. Scheirer

CoRR, 2023

Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent.

Vineet R. Shenoy, Tim K. Marks, Hassan Mansour, Suhas Lohit

Proceedings of the IEEE International Conference on Image Processing, 2023

Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection.

Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael N. Jones

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis.

Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks.

Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga

Proceedings of the IEEE International Conference on Acoustics, 2023

Are Deep Neural Networks SMARTer Than Second Graders?

Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Model Compression Using Optimal Transport.

Suhas Lohit, Michael Jones

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective.

Huan Wang, Suhas Lohit, Michael N. Jones, Yun Fu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Partial Equivariances From Data.

David W. Romero, Suhas Lohit

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Distributed Radar Autofocus Imaging Using Deep Priors.

Hassan Mansour, Suhas Lohit, Petros T. Boufounos

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Cross-Modal Knowledge Transfer Without Task-Relevant Source Data.

Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael Jones, Amit K. Roy-Chowdhury

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Learning Equivariances and Partial Equivariances from Data.

David W. Romero, Suhas Lohit

CoRR, 2021

Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization.

Suhas Lohit, Rushil Anirudh, Pavan K. Turaga

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Generative Patch Priors for Practical Compressive Image Recovery.

Rushil Anirudh, Suhas Lohit, Pavan K. Turaga

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Turnip: Time-Series U-Net With Recurrence For NIR Imaging PPG.

Armand Comas, Tim K. Marks, Hassan Mansour, Suhas Lohit, Yechi Ma, Xiaoming Liu

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

Rotation-Invariant Autoencoders for Signals on Spheres.

Suhas Lohit, Shubhendu Trivedi

CoRR, 2020

Multi-head Knowledge Distillation for Model Compression.

Huan Wang, Suhas Lohit, Michael Jones, Yun Fu

CoRR, 2020

Knowledge Distillation Thrives on Data Augmentation.

Huan Wang, Suhas Lohit, Michael Jones, Yun Fu

CoRR, 2020

Rate-Invariant Autoencoding of Time-Series.

Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Unrolled Projected Gradient Descent for Multi-spectral Image Fusion.

Suhas Lohit, Dehong Liu, Hassan Mansour, Petros T. Boufounos

Proceedings of the IEEE International Conference on Acoustics, 2019

Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping.

Suhas Lohit, Qiao Wang, Pavan K. Turaga

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Rank-Regularized Measurement Operators for Compressive Imaging.

Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images.

Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok

IEEE Trans. Computational Imaging, 2018

Rate-Adaptive Neural Networks for Spatial Multiplexers.

Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga

CoRR, 2018

CS-VQA: Visual Question Answering with Compressively Sensed Images.

Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Predicting Dynamical Evolution of Human Activities From a Single Image.

Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker K. Pillai, Pavan K. Turaga, Rama Chellappa

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images.

Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok

CoRR, 2017

Learning Invariant Riemannian Geometric Representations Using Deep Nets.

Suhas Lohit, Pavan K. Turaga

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016

ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements.

Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok

CoRR, 2016

Direct inference on compressive measurements using convolutional neural networks.

Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer.

Qiao Wang, Suhas Lohit, Meynard John Toledo, Matthew P. Buman, Pavan K. Turaga

Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements.

Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Reconstruction-free inference on compressive measurements.

Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga, Jian Wang, Aswin C. Sankaranarayanan

Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2015