7 papers
Avatar V: Scaling Video-Reference Avatar Video Generation
Benjamin Liang, Ce Chen, Desmond Lin +20
Generating avatar videos that are not merely visually similar to a target individual but behaviorally recognizable, faithfully reproducing their talking rhythm, gestural tendencies…
TransVLM: A Vision-Language Framework and Benchmark for Detecting Any Shot Transitions
Ce Chen, Yi Ren, Yuanming Li +5
Traditional Shot Boundary Detection (SBD) inherently struggles with complex transitions by formulating the task around isolated cut points, frequently yielding corrupted video shot…
Generate Your Talking Avatar from Video Reference
Zujin Guo, Zhenhui Ye, Yi Ren +4
Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target generation. This restricted,…
SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer
Jimin Xu, Bosheng Qin, Tao Jin +4
Recent advancements in neural representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have increased interest in applying style transfer to 3D scenes. While exis…
HumanDiT: Pose-Guided Diffusion Transformer for Long-form Human Motion Video Generation
Qijun Gan, Yi Ren, Chen Zhang +6
Human motion video generation has advanced significantly, while existing methods still struggle with accurately rendering detailed body parts like hands and faces, especially in lo…
T2A-Feedback: Improving Basic Capabilities of Text-to-Audio Generation via Fine-grained AI Feedback
Zehan Wang, Ke Lei, Chen Zhu +8
Text-to-audio (T2A) generation has achieved remarkable progress in generating a variety of audio outputs from language prompts. However, current state-of-the-art T2A models still s…