49 citations · 99 across the 7 of their papers we have counts for
7 papers · 1 filter
Extending Video Masked Autoencoders to 128 frames
Nitesh Bharadwaj Gundavarapu, Luke Friedman, Raghav Goyal +8
Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked…
VideoPrism: A Foundational Visual Encoder for Video Understanding
Long Zhao, Nitesh B. Gundavarapu, Liangzhe Yuan +16
We introduce VideoPrism, a general-purpose video encoder that tackles diverse video understanding tasks with a single frozen model. We pretrain VideoPrism on a heterogeneous corpus…
Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation
Lijun Yu, José Lezama, Nitesh B. Gundavarapu +13
While Large Language Models (LLMs) are the dominant models for generative tasks in language, they do not perform as well as diffusion models on image and video generation. To effec…
VideoGLUE: Video General Understanding Evaluation of Foundation Models
Liangzhe Yuan, Nitesh Bharadwaj Gundavarapu, Long Zhao +14
We evaluate the video understanding capabilities of existing foundation models (FMs) using a carefully designed experiment protocol consisting of three hallmark tasks (action recog…
Test-Time Personalization with a Transformer for Human Pose Estimation
Yizhuo Li, Miao Hao, Zonglin Di +2
We propose to personalize a human pose estimator given a set of test images of a person without using any manual annotations. While there is a significant advancement in human pose…
Multi-Person 3D Human Pose Estimation from Monocular Images
Rishabh Dabral, Nitesh B Gundavarapu, Rahul Mitra +3
Multi-person 3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data. We propose HG-RCNN, a…
Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation
Rahul Mitra, Nitesh B. Gundavarapu, Abhishek Sharma +1
The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly an…