Egocentric Scene Graphs convert long videos into short structured text so MLLMs can answer questions about entire sequences, achieving SOTA on HD-EPIC VQA.
arXiv preprint arXiv:2502.16427 (2025)
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SG-Ego dataset and GLEN model enable structured reasoning over spatio-temporal scene graphs for ego-centric activity understanding, introducing the A-GEF forecasting task.
This is a survey that frames video MLLM research via a human-view formulation of perceptual representations, memory states, reasoning traces, and predictions, then reviews methods, datasets, benchmarks, and open problems.
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Graph it first! Enabling Reasoning on Long-form Egocentric Videos through Scene Graphs
Egocentric Scene Graphs convert long videos into short structured text so MLLMs can answer questions about entire sequences, achieving SOTA on HD-EPIC VQA.
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Learning to Evolve Scenes: Reasoning about Human Activities with Scene Graphs
SG-Ego dataset and GLEN model enable structured reasoning over spatio-temporal scene graphs for ego-centric activity understanding, introducing the A-GEF forecasting task.
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Watch, Remember, Reason: Human-View Video Understanding with MLLMs
This is a survey that frames video MLLM research via a human-view formulation of perceptual representations, memory states, reasoning traces, and predictions, then reviews methods, datasets, benchmarks, and open problems.