6 papers
DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation
Mingji Ge, Qirui Chen, Zeqian Li +1
Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora, like HowTo100M, offer rich…
See, Remember, Explore: A Benchmark and Baselines for Streaming Spatial Reasoning
Yuxi Wei, Wei Huang, Qirui Chen +2
Spatial understanding is fundamental for embodied agents, yet most spatial VLMs and benchmarks remain offline-evaluating post-hoc QA over pre-recorded inputs and overlooking two cr…
Weaver: End-to-End Agentic System Training for Video Interleaved Reasoning
Yudi Shi, Shangzhe Di, Qirui Chen +5
Video reasoning constitutes a comprehensive assessment of a model's capabilities, as it demands robust perceptual and interpretive skills, thereby serving as a means to explore the…
Object-centric Video Question Answering with Visual Grounding and Referring
Haochen Wang, Qirui Chen, Cilin Yan +5
Video Large Language Models (VideoLLMs) have recently demonstrated remarkable progress in general video understanding. However, existing models primarily focus on high-level compre…
Learning Streaming Video Representation via Multitask Training
Yibin Yan, Jilan Xu, Shangzhe Di +6
Understanding continuous video streams plays a fundamental role in real-time applications including embodied AI and autonomous driving. Unlike offline video understanding, streamin…
Enhancing Video-LLM Reasoning via Agent-of-Thoughts Distillation
Yudi Shi, Shangzhe Di, Qirui Chen +1
This paper tackles the problem of video question answering (VideoQA), a task that often requires multi-step reasoning and a profound understanding of spatial-temporal dynamics. Whi…