Text-to-video (T2V) diffusion models can reproduce copyrighted, violent, or explicit content, which motivates concept erasure: removing designated concepts from a pretrained model while preserving its behavior on everything else. Existing T2V erasure methods leave two problems open. Their frame-agnostic suppression can...
Yu-Chen Li, Kai-Yuan Deng, Chaoran Feng et al.· 0 citations
UniSandbox, a decoupled evaluation framework paired with controlled, synthetic datasets to avoid data leakage and enable detailed analysis, reveals a significant understanding-generation gap, which is mainly reflected in two key dimensions: reasoning generation and knowledge transfer.
WorldCrafter is a video world model that learns a camera-queryable implicit 3D-aware memory that enables streaming scene exploration from a single input image or text prompt and shows substantial gains in long-horizon consistency and camera-control accuracy while preserving visual quality during minute-scale exploratio...
Wang-Bo Yu, Kun-Hao Liu, Wen-Bo Hu et al.· 1 citation
UniWorld-View is introduced, a unified framework for controllable large-baseline novel view synthesis from monocular inputs that integrates explicit 3D guidance with generative diffusion modeling to enable precise camera control and geometrically consistent view generation.
Hai-Yang Zhou, Wang-Bo Yu, Chaoran Feng et al.· 2 citations
LingBot-Video is presented, a DiT-based video pretraining paradigm specifically tailored for embodied intelligence, and is contributed as the inaugural large-scale, open-source MoE video foundation model to the community, in a pioneering effort to bridge digital creativity and physical actuation.
Shuailei Ma, Jiaqi Liao, Xinyang Wang et al.· 7 citations· ⚡1
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