Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction. - Max Ehrlich; Jon Barker; Namitha Padmanabhan; Larry Davis 001; Andrew Tao; Bryan Catanzaro; Abhinav Shrivastava (CoRR, 2022)

Diffusion Models Beat GANs on Image Classification. - Soumik Mukhopadhyay 001; Matthew Gwilliam; Vatsal Agarwal; Namitha Padmanabhan; Archana Swaminathan; Srinidhi Hegde; Tianyi Zhou 001; Abhinav Shrivastava (CoRR, 2023)

Do text-free diffusion models learn discriminative visual representations? - Soumik Mukhopadhyay 001; Matthew Gwilliam; Yosuke Yamaguchi; Vatsal Agarwal; Namitha Padmanabhan; Archana Swaminathan; Tianyi Zhou 001; Abhinav Shrivastava (CoRR, 2023)

Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing Their Contributions. - Namitha Padmanabhan; Matthew Gwilliam; Pulkit Kumar; Shishira R. Maiya; Max Ehrlich; Abhinav Shrivastava (CVPR, 2024)

Trajectory-Aligned Space-Time Tokens for Few-Shot Action Recognition. - Pulkit Kumar; Namitha Padmanabhan; Luke Luo; Sai Saketh Rambhatla; Abhinav Shrivastava (ECCV (36), 2024)

Do Text-Free Diffusion Models Learn Discriminative Visual Representations? - Soumik Mukhopadhyay 001; Matthew Gwilliam; Yosuke Yamaguchi; Vatsal Agarwal; Namitha Padmanabhan; Archana Swaminathan; Tianyi Zhou 001; Jun Ohya; Abhinav Shrivastava (ECCV (60), 2024)

Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement. - Max Ehrlich; Jon Barker; Namitha Padmanabhan; Larry Davis 001; Andrew Tao; Bryan Catanzaro; Abhinav Shrivastava (WACV, 2024)

How to Design and Train Your Implicit Neural Representation for Video Compression. - Matthew Gwilliam; Roy Zhang; Namitha Padmanabhan; Hongyang Du; Abhinav Shrivastava (CoRR, 2025)