6 papers
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…
MINERVA: Evaluating Complex Video Reasoning
Arsha Nagrani, Sachit Menon, Ahmet Iscen +9
Multimodal LLMs are turning their focus to video benchmarks, however most video benchmarks only provide outcome supervision, with no intermediate or interpretable reasoning steps.…
Neptune: The Long Orbit to Benchmarking Long Video Understanding
Arsha Nagrani, Mingda Zhang, Ramin Mehran +10
We introduce Neptune, a benchmark for long video understanding that requires reasoning over long time horizons and across different modalities. Many existing video datasets and mod…
SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset
Sagar M. Waghmare, Kimberly Wilber, Dave Hawkey +9
Vision is essential for human navigation. The World Health Organization (WHO) estimates that 43.3 million people were blind in 2020, and this number is projected to reach 61 millio…
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…
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…