Suhas Lohit - RankMe

69 papers A* 9A 4B 5Misc 4Journal 37Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Recovering Pulse Waves From Video Using Deep Unrolling and Deep Equilibrium Models. IEEE Trans. Image Process. Vineet R. Shenoy, Suhas Lohit, Hassan Mansour, Rama Chellappa, Tim K. Marks
2026	J	`jnl`	Understanding Dynamic Compute Allocation in Recurrent Transformers. CoRR Ibraheem Muhammad Moosa, Suhas Lohit, Ye Wang, Moitreya Chatterjee, Wenpeng Yin
2025	J	`jnl`	Auto-Vocabulary 3D Object Detection. CoRR Haomeng Zhang, Kuan-Chuan Peng, Suhas Lohit, Raymond A. Yeh
2025	—	`conf`	FreBIS: Frequency-Based Stratification for Neural Implicit Surface Representations. CVPR Workshops Naoko Sawada, Pedro Miraldo, Suhas Lohit, Tim K. Marks, Moitreya Chatterjee
2025	J	`jnl`	FreBIS: Frequency-Based Stratification for Neural Implicit Surface Representations. CoRR Naoko Sawada, Pedro Miraldo, Suhas Lohit, Tim K. Marks, Moitreya Chatterjee
2025	J	`jnl`	G-RepsNet: A Lightweight Construction of Equivariant Networks for Arbitrary Matrix Groups. Trans. Mach. Learn. Res. Sourya Basu, Suhas Lohit, Matthew Brand
2025	—	`conf`	Multimodal 3D Object Detection on Unseen Domains. CVPR Workshops Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael Jones, Vishal Patel
2025	J	`jnl`	Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal. CoRR Yuyang Hu, Suhas Lohit, Ulugbek S. Kamilov, Tim K. Marks
2025	J	`jnl`	Programmatic Video Prediction Using Large Language Models. CoRR Hao Tang, Kevin Ellis, Suhas Lohit, Michael J. Jones, Moitreya Chatterjee
2025	J	`jnl`	Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models. CoRR Vineet R. Shenoy, Suhas Lohit, Hassan Mansour, Rama Chellappa, Tim K. Marks
2025	J	`jnl`	Time-Series U-Net With Recurrence for Noise-Robust Imaging Photoplethysmography. IEEE Access Vineet R. Shenoy, Shaoju Wu, Armand Comas, Suhas Lohit, Hassan Mansour, Tim K. Marks
2025	J	`jnl`	Time-Series U-Net with Recurrence for Noise-Robust Imaging Photoplethysmography. CoRR Vineet R. Shenoy, Shaoju Wu, Armand Comas, Tim K. Marks, Suhas Lohit, Hassan Mansour
2025	J	`jnl`	Towards Open-Vocabulary Multimodal 3D Object Detection with Attributes. CoRR Xinhao Xiang, Kuan-Chuan Peng, Suhas Lohit, Michael J. Jones, Jiawei Zhang
2025	J	`jnl`	WISE: Weighted Iterative Society-of-Experts for Robust Multimodal Multi-Agent Debate. CoRR Anoop Cherian, River Doyle, Eyal Ben-Dov, Suhas Lohit, Kuan-Chuan Peng
2024	J	`jnl`	Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection. CoRR Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel
2024	—	`conf`	Equivariant Spatio-temporal Self-supervision for LiDAR Object Detection. ECCV (26) Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel
2024	A*	`conf`	Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. NeurIPS Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin A. Smith, Josh Tenenbaum
2024	J	`jnl`	Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. CoRR Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin Smith, Joshua B. Tenenbaum
2024	J	`jnl`	G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups. CoRR Sourya Basu, Suhas Lohit, Matthew Brand
2024	A*	`conf`	Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-Aware Spatio-Temporal Sampling. CVPR Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang, Pedro Miraldo, Suhas Lohit, Moitreya Chatterjee
2024	J	`jnl`	Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling. CoRR Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang, Pedro Miraldo, Suhas Lohit, Moitreya Chatterjee
2024	J	`jnl`	Multimodal 3D Object Detection on Unseen Domains. CoRR Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel
2024	A	`conf`	Pixel-Grounded Prototypical Part Networks. WACV Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer
2024	—	`conf`	Rotation-Equivariant Neural Networks for Cloud Removal from Satellite Images. IEEECONF Suhas Lohit, Tim K. Marks
2024	A*	`conf`	TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. CVPR Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks
2024	J	`jnl`	TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. CoRR Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks
2023	A*	`conf`	Are Deep Neural Networks SMARTer Than Second Graders? CVPR Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum
2023	J	`jnl`	Pixel-Grounded Prototypical Part Networks. CoRR Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer
2023	Misc	`conf`	Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. ICASSP Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2023	A*	`conf`	Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. ICCV Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks
2023	J	`jnl`	Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. CoRR Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks
2023	—	`conf`	Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. ICCV (Workshops) Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael J. Jones
2023	J	`jnl`	Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. CoRR Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael Jones
2023	B	`conf`	Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent. ICIP Vineet R. Shenoy, Tim K. Marks, Hassan Mansour, Suhas Lohit
2022	J	`jnl`	Are Deep Neural Networks SMARTer than Second Graders? CoRR Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum
2022	—	`conf`	Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. ECCV (34) Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael Jones, Amit K. Roy-Chowdhury
2022	J	`jnl`	Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. CoRR Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Amit K. Roy-Chowdhury
2022	B	`conf`	Distributed Radar Autofocus Imaging Using Deep Priors. ICIP Hassan Mansour, Suhas Lohit, Petros T. Boufounos
2022	A*	`conf`	Learning Partial Equivariances From Data. NeurIPS David W. Romero, Suhas Lohit
2022	A	`conf`	Model Compression Using Optimal Transport. WACV Suhas Lohit, Michael Jones
2022	A*	`conf`	What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective. NeurIPS Huan Wang, Suhas Lohit, Michael J. Jones, Yun Fu
2021	A	`conf`	Generative Patch Priors for Practical Compressive Image Recovery. WACV Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
2021	J	`jnl`	Learning Equivariances and Partial Equivariances from Data. CoRR David W. Romero, Suhas Lohit
2021	A	`conf`	Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. WACV Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2021	B	`conf`	Turnip: Time-Series U-Net With Recurrence For NIR Imaging PPG. ICIP Armand Comas, Tim K. Marks, Hassan Mansour, Suhas Lohit, Yechi Ma, Xiaoming Liu
2020	J	`jnl`	Generative Patch Priors for Practical Compressive Image Recovery. CoRR Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
2020	J	`jnl`	Knowledge Distillation Thrives on Data Augmentation. CoRR Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
2020	J	`jnl`	Model Compression Using Optimal Transport. CoRR Suhas Lohit, Michael Jones
2020	J	`jnl`	Multi-head Knowledge Distillation for Model Compression. CoRR Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
2020	Misc	`conf`	Rate-Invariant Autoencoding of Time-Series. ICASSP Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2020	J	`jnl`	Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. CoRR Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
2020	J	`jnl`	Rotation-Invariant Autoencoders for Signals on Spheres. CoRR Suhas Lohit, Shubhendu Trivedi
2019	Misc	`conf`	Rank-Regularized Measurement Operators for Compressive Imaging. ACSSC Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga
2019	A*	`conf`	Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CVPR Suhas Lohit, Qiao Wang, Pavan K. Turaga
2019	J	`jnl`	Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CoRR Suhas Lohit, Qiao Wang, Pavan K. Turaga
2019	Misc	`conf`	Unrolled Projected Gradient Descent for Multi-spectral Image Fusion. ICASSP Suhas Lohit, Dehong Liu, Hassan Mansour, Petros T. Boufounos
2018	B	`conf`	CS-VQA: Visual Question Answering with Compressively Sensed Images. ICIP Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga
2018	J	`jnl`	CS-VQA: Visual Question Answering with Compressively Sensed Images. CoRR Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga
2018	J	`jnl`	Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images. IEEE Trans. Computational Imaging Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok
2018	—	`conf`	Predicting Dynamical Evolution of Human Activities From a Single Image. CVPR Workshops Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker K. Pillai, Pavan K. Turaga, Rama Chellappa
2018	J	`jnl`	Rate-Adaptive Neural Networks for Spatial Multiplexers. CoRR Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga
2017	J	`jnl`	Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images. CoRR Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok
2017	—	`conf`	Learning Invariant Riemannian Geometric Representations Using Deep Nets. ICCV Workshops Suhas Lohit, Pavan K. Turaga
2017	J	`jnl`	Learning Invariant Riemannian Geometric Representations Using Deep Nets. CoRR Suhas Lohit, Pavan K. Turaga
2016	—	`conf`	A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer. EMBC Qiao Wang, Suhas Lohit, Meynard John Toledo, Matthew P. Buman, Pavan K. Turaga
2016	B	`conf`	Direct inference on compressive measurements using convolutional neural networks. ICIP Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga
2016	A*	`conf`	ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements. CVPR Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok
2016	J	`jnl`	ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements. CoRR Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok
2015	—	`conf`	Reconstruction-free inference on compressive measurements. CVPR Workshops Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga, Jian Wang, Aswin C. Sankaranarayanan