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…
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…
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…