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cs.CV2026

VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding

Fan Zhang, Guangming Yao, Jinyang Wu +6

Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approx…

cs.CV2026

GroupVideo: Multi-Identity Customized Text-to-Video Generation

Xinyang Song, Libin Wang, Jianxin Sun +4

Current identity customized video generation methodologies are predominantly limited to single-identity scenarios, as the lack of explicit identity separation mechanisms often lead…

cs.CV2026

MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism

Cong Chen, Guo Gan, Kaixiang Ji +7

Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overco…

cs.CV2026

ACTIVE-o3: Empowering MLLMs with Active Perception via Pure Reinforcement Learning

Muzhi Zhu, Hao Zhong, Canyu Zhao +9

Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant information. It is a critical component of effic…

cs.CV2026

SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation

Shuai Tan, Biao Gong, Yujie Wei +8

Diffusion-based video motion customization facilitates the acquisition of human motion representations from a few video samples, while achieving arbitrary subjects transfer through…

cs.CV2026

VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation

Longteng Jiang, DanDan Zheng, Qianqian Qiao +7

The rapid advancement of AIGC-based video generation has underscored the critical need for comprehensive evaluation frameworks that go beyond traditional generation quality metrics…