9 papers
Emotion-Cause Pair Extraction in Conversations via Semantic Decoupling and Graph Alignment
Tianxiang Ma, Weijie Feng, Xinyu Wang +1
Emotion-Cause Pair Extraction in Conversations (ECPEC) aims to identify the set of causal relations between emotion utterances and their triggering causes within a dialogue. Most e…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
LibraGen: Playing a Balance Game in Subject-Driven Video Generation
Jiahao Zhu, Shanshan Lao, Lijie Liu +10
With the advancement of video generation foundation models (VGFMs), customized generation, particularly subject-to-video (S2V), has attracted growing attention. However, a key chal…
OmniInsert: Mask-Free Video Insertion of Any Reference via Diffusion Transformer Models
Jinshu Chen, Xinghui Li, Xu Bai +8
Recent advances in video insertion based on diffusion models are impressive. However, existing methods rely on complex control signals but struggle with subject consistency, limiti…
HuMo: Human-Centric Video Generation via Collaborative Multi-Modal Conditioning
Liyang Chen, Tianxiang Ma, Jiawei Liu +7
Human-Centric Video Generation (HCVG) methods seek to synthesize human videos from multimodal inputs, including text, image, and audio. Existing methods struggle to effectively coo…
I2VControl: Disentangled and Unified Video Motion Synthesis Control
Wanquan Feng, Tianhao Qi, Jiawei Liu +7
Motion controllability is crucial in video synthesis. However, most previous methods are limited to single control types, and combining them often results in logical conflicts. In…