VideoOdyssey: A Benchmark for Ultra-Long-Context and Omni-Modal Video Understanding
VideoOdyssey is a benchmark for ultra-long-context and omni-modal video understanding, featuring videos averaging 109 minutes across 11 domains and 54 subcategories. It measures cognitive load via continuous certificate length and offers five granular levels. Evaluations show current MLLMs struggle with continuous reasoning, fine-grained perception, and non-verbal omni-modal understanding.
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Key points
- Introduces continuous certificate length to measure reasoning ability over ultra-long videos.
- Includes visual-only (VideoOdyssey-V) and audio-visual (VideoOdyssey-AV) subsets.
- Average continuous certificate length of 16 min for V and 12.8 min for AV, with five temporal granularities.
- Current models show limitations in continuous reasoning, fine-grained perception, and non-verbal understanding.
Why it matters
This matters because introduces continuous certificate length to measure reasoning ability over ultra-long videos.
Technical impact
May affect model selection, inference cost, product capability, and evaluation benchmarks.
[2605.22907] VideoOdyssey: A Benchmark for Ultra-Long-Context and Omni-Modal Video Understanding
[Submitted on 21 May 2026]
Title:VideoOdyssey: A Benchmark for Ultra-Long-Context and Omni-Modal Video Understanding
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Abstract:Real-world long video understanding requires models to perform continuous tracking, information integration and memory retention over massive temporal spans within extreme video durations. Mastering this intense cognitive load constitutes the fundamental bottleneck in long video understanding. While existing benchmarks have driven progress by scaling up video duration, their evaluation tasks often require comprehending only short and isolated video segments, falling short of capturing the challenge of ultra-long-context reasoning. To measure this cognitive load, we emphasize continuous certificate length, defined as the video length a human must continuously watch to definitively answer a given question. Driven by this metric, we introduce VideoOdyssey, a benchmark specifically designed for ultra-long-context and omni-modal video understanding. VideoOdyssey is characterized by three key features: 1) Extreme video duration and diversity: spanning 11 domains and 54 subcategories with an average video duration of 109 minutes; 2) Comprehensive evaluation scenarios: offering two subsets to address different research focuses, i.e., VideoOdyssey-V for probing the limits of visual understanding in MLLMs, and VideoOdyssey-AV for evaluating synchronized audio-visual understanding for omni-modal models; 3) Ultra-long and multi-level continuous certificates: extending the average continuous certificate to 16 minutes for VideoOdyssey-V and 12.8 minutes for VideoOdyssey-AV. Crucially, we design 5 granular levels from seconds to hours, providing a comprehensive diagnostic tool to evaluate models across varying context lengths and cognitive loads. Extensive evaluations show that bottlenecks of current MLLMs extend beyond simple retrieval to include struggles with continuous reasoning across varying context lengths, fine-grained perception, and non-verbal omni-modal understanding.
Subjects:
Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2605.22907 [cs.CV]
(or arXiv:2605.22907v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2605.22907
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Haichen He [view email] [v1] Thu, 21 May 2026 18:00:22 UTC (12,663 KB)
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