7 papers
Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding
Arsha Nagrani, Jasper Uijilings, Shyamal Buch +6
Video reasoning models are a core component of egocentric and embodied agents. However, standard benchmarks for assessing models provide only evaluation of the output (e.g. the ans…
MINERVA-Cultural: A Benchmark for Cultural and Multilingual Long Video Reasoning
Darshan Singh, Arsha Nagrani, Kawshik Manikantan +6
Recent advancements in video models have shown tremendous progress, particularly in long video understanding. However, current benchmarks predominantly feature western-centric data…
CAViAR: Critic-Augmented Video Agentic Reasoning
Sachit Menon, Ahmet Iscen, Arsha Nagrani +3
Video understanding has seen significant progress in recent years, with models' performance on perception from short clips continuing to rise. Yet, multiple recent benchmarks, such…
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…