collaborators

5 papers

eess.AS2026

CAD: Conflict-Aware Decoding to Mitigate Cross-Modal Hallucinations in Omnimodal Large Language Models

Yuchen Deng, Chang Sun, Hai-Tao Zheng +2

Omnimodal large language models (Omni-LLMs) integrate audio, video, and text, yet remain vulnerable to cross-modal hallucinations, where one modality improperly influences predicti…

cs.CV2026

GeoEdit: Geometry-Aware Object Editing via Dual-Branch Denoising

Yi He, Jiangming Wang, Xinyu Wang +5

Precisely manipulating objects in a single photograph (translation, rotation, scaling) while obeying 3D physical constraints remains unsolved for diffusion-based editors. Current 2…

cs.AI2026

OmniRefine: Alignment-Aware Cooperative Compression for Efficient Omnimodal Large Language Models

Yuchen Deng, Zidang Cai, Hai-Tao Zheng +3

Omnimodal large language models (Omni-LLMs) show strong capability in audio-video understanding, but their practical deployment remains limited by high inference cost of long video…

cs.CV2025

Beyond Boundary Frames: Talking-Head Inbetweening via Context-Aware Motion Modeling

Yuchen Deng, Hai-Tao Zheng, Jie Wang +3

Existing talking-head generation methods primarily target open-ended generation rather than bridging two existing video segments. In this paper, we study talking-head inbetweening,…

cs.CV2025

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling

Yuchen Deng, Xiuyang Wu, Hai-Tao Zheng +3

Current talking-head generation has gradually shifted from GAN-based methods to diffusion-based paradigms, achieving remarkable progress in visual fidelity and temporal consistency…