5 papers
Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models
Meiqi Wu, Zhixin Cai, Fufangchen Zhao +13
Video--based world models have emerged along two dominant paradigms: video generation and 3D reconstruction. However, existing evaluation benchmarks either focus narrowly on visual…
Latent Temporal Discrepancy as Motion Prior: A Loss-Weighting Strategy for Dynamic Fidelity in T2V
Meiqi Wu, Bingze Song, Ruimin Lin +5
Video generation models have achieved notable progress in static scenarios, yet their performance in motion video generation remains limited, with quality degrading under drastic d…
Artifact-Aware Evaluation for High-Quality Video Generation
Chen Zhu, Jiashu Zhu, Yanxun Li +6
With the rapid advancement of video generation techniques, evaluating and auditing generated videos has become increasingly crucial. Existing approaches typically offer coarse vide…
Taming Hallucinations: Boosting MLLMs' Video Understanding via Counterfactual Video Generation
Zhe Huang, Hao Wen, Aiming Hao +6
Multimodal Large Language Models (MLLMs) have made remarkable progress in video understanding. However, they suffer from a critical vulnerability: an over-reliance on language prio…
ImagerySearch: Adaptive Test-Time Search for Video Generation Beyond Semantic Dependency Constraints
Meiqi Wu, Jiashu Zhu, Xiaokun Feng +7
Video generation models have achieved remarkable progress, particularly excelling in realistic scenarios; however, their performance degrades notably in imaginative scenarios. Thes…