Suhas Lohit

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 49

Top Topics

Human Activities

Iterative Reconstruction

Image Synthesis

Top Venues

Publications

Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Joanna Matthiesen, Kevin Smith, Joshua B. Tenenbaum
Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads. CoRR (2024)
Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael J. Jones, Walter J. Scheirer
Pixel-Grounded Prototypical Part Networks. WACV (2024)
Sourya Basu, Suhas Lohit, Matthew Brand
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups. CoRR (2024)
Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel
Multimodal 3D Object Detection on Unseen Domains. CoRR (2024)
Xinhang Liu, Yu-Wing Tai, Chi-Keung Tang, Pedro Miraldo, Suhas Lohit, Moitreya Chatterjee
Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling. CoRR (2024)
Haomiao Ni, Bernhard Egger, Suhas Lohit, Anoop Cherian, Ye Wang, Toshiaki Koike-Akino, Sharon X. Huang, Tim K. Marks
TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. CoRR (2024)
Deepti Hegde, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Vishal M. Patel
Equivariant Spatio-Temporal Self-Supervision for LiDAR Object Detection. CoRR (2024)
Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks
Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. ICCV (2023)
Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael N. Jones
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. ICCV (Workshops) (2023)
Manish Sharma, Moitreya Chatterjee, Kuan-Chuan Peng, Suhas Lohit, Michael Jones
Tensor Factorization for Leveraging Cross-Modal Knowledge in Data-Constrained Infrared Object Detection. CoRR (2023)
Zachariah Carmichael, Suhas Lohit, Anoop Cherian, Michael N. Jones, Walter J. Scheirer
Pixel-Grounded Prototypical Part Networks. CoRR (2023)
Eun Som Jeon, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Robust Time Series Recovery and Classification Using Test-Time Noise Simulator Networks. ICASSP (2023)
Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum
Are Deep Neural Networks SMARTer Than Second Graders? CVPR (2023)
Nithin Gopalakrishnan Nair, Anoop Cherian, Suhas Lohit, Ye Wang, Toshiaki Koike-Akino, Vishal M. Patel, Tim K. Marks
Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. CoRR (2023)
Vineet R. Shenoy, Tim K. Marks, Hassan Mansour, Suhas Lohit
Unrolled iPPG: Video Heart Rate Estimation via Unrolling Proximal Gradient Descent. ICIP (2023)
Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael Jones, Amit K. Roy-Chowdhury
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. ECCV (34) (2022)
David W. Romero, Suhas Lohit
Learning Partial Equivariances From Data. NeurIPS (2022)
Anoop Cherian, Kuan-Chuan Peng, Suhas Lohit, Kevin A. Smith, Joshua B. Tenenbaum
Are Deep Neural Networks SMARTer than Second Graders? CoRR (2022)
Hassan Mansour, Suhas Lohit, Petros T. Boufounos
Distributed Radar Autofocus Imaging Using Deep Priors. ICIP (2022)
Suhas Lohit, Michael Jones
Model Compression Using Optimal Transport. WACV (2022)
Huan Wang, Suhas Lohit, Michael N. Jones, Yun Fu
What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective. NeurIPS (2022)
Sk Miraj Ahmed, Suhas Lohit, Kuan-Chuan Peng, Michael J. Jones, Amit K. Roy-Chowdhury
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data. CoRR (2022)
Armand Comas, Tim K. Marks, Hassan Mansour, Suhas Lohit, Yechi Ma, Xiaoming Liu
Turnip: Time-Series U-Net With Recurrence For NIR Imaging PPG. ICIP (2021)
Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. WACV (2021)
David W. Romero, Suhas Lohit
Learning Equivariances and Partial Equivariances from Data. CoRR (2021)
Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
Generative Patch Priors for Practical Compressive Image Recovery. WACV (2021)
Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
Knowledge Distillation Thrives on Data Augmentation. CoRR (2020)
Huan Wang, Suhas Lohit, Michael Jones, Yun Fu
Multi-head Knowledge Distillation for Model Compression. CoRR (2020)
Suhas Lohit, Michael Jones
Model Compression Using Optimal Transport. CoRR (2020)
Suhas Lohit, Shubhendu Trivedi
Rotation-Invariant Autoencoders for Signals on Spheres. CoRR (2020)
Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization. CoRR (2020)
Kaushik Koneripalli, Suhas Lohit, Rushil Anirudh, Pavan K. Turaga
Rate-Invariant Autoencoding of Time-Series. ICASSP (2020)
Rushil Anirudh, Suhas Lohit, Pavan K. Turaga
Generative Patch Priors for Practical Compressive Image Recovery. CoRR (2020)
Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga
Rank-Regularized Measurement Operators for Compressive Imaging. ACSSC (2019)
Suhas Lohit, Dehong Liu, Hassan Mansour, Petros T. Boufounos
Unrolled Projected Gradient Descent for Multi-spectral Image Fusion. ICASSP (2019)
Suhas Lohit, Qiao Wang, Pavan K. Turaga
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CVPR (2019)
Suhas Lohit, Qiao Wang, Pavan K. Turaga
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping. CoRR (2019)
Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga
CS-VQA: Visual Question Answering with Compressively Sensed Images. CoRR (2018)
Li-Chi Huang, Kuldeep Kulkarni, Anik Jha, Suhas Lohit, Suren Jayasuriya, Pavan K. Turaga
CS-VQA: Visual Question Answering with Compressively Sensed Images. ICIP (2018)
Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok
Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images. IEEE Trans. Computational Imaging 4 (3) (2018)
Suhas Lohit, Rajhans Singh, Kuldeep Kulkarni, Pavan K. Turaga
Rate-Adaptive Neural Networks for Spatial Multiplexers. CoRR (2018)
Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker K. Pillai, Pavan K. Turaga, Rama Chellappa
Predicting Dynamical Evolution of Human Activities From a Single Image. CVPR Workshops (2018)
Suhas Lohit, Pavan K. Turaga
Learning Invariant Riemannian Geometric Representations Using Deep Nets. ICCV Workshops (2017)
Suhas Lohit, Pavan K. Turaga
Learning Invariant Riemannian Geometric Representations Using Deep Nets. CoRR (2017)
Suhas Lohit, Kuldeep Kulkarni, Ronan Kerviche, Pavan K. Turaga, Amit Ashok
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images. CoRR (2017)
Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements. CVPR (2016)
Qiao Wang, Suhas Lohit, Meynard John Toledo, Matthew P. Buman, Pavan K. Turaga
A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer. EMBC (2016)
Kuldeep Kulkarni, Suhas Lohit, Pavan K. Turaga, Ronan Kerviche, Amit Ashok
ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements. CoRR (2016)
Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga
Direct inference on compressive measurements using convolutional neural networks. ICIP (2016)
Suhas Lohit, Kuldeep Kulkarni, Pavan K. Turaga, Jian Wang, Aswin C. Sankaranarayanan
Reconstruction-free inference on compressive measurements. CVPR Workshops (2015)