1 citations · 1 across the 3 of their papers we have counts for
6 papers
ReImagine: Rethinking Controllable High-Quality Human Video Generation via Image-First Synthesis
Zhengwentai Sun, Keru Zheng, Chenghong Li +7
Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-view data. Existing methods…
Condition Matters in Full-head 3D GANs
Heyuan Li, Huimin Zhang, Yuda Qiu +10
Conditioning is crucial for stable training of full-head 3D GANs. Without any conditioning signal, the model suffers from severe mode collapse, making it impractical to training. H…
MV-Performer: Taming Video Diffusion Model for Faithful and Synchronized Multi-view Performer Synthesis
Yihao Zhi, Chenghong Li, Hongjie Liao +6
Recent breakthroughs in video generation, powered by large-scale datasets and diffusion techniques, have shown that video diffusion models can function as implicit 4D novel view sy…
Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets
Weiyu Li, Xuanyang Zhang, Zheng Sun +15
While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamen…
MVHumanNet++: A Large-scale Dataset of Multi-view Daily Dressing Human Captures with Richer Annotations for 3D Human Digitization
Chenghong Li, Hongjie Liao, Yihao Zhi +5
In this era, the success of large language models and text-to-image models can be attributed to the driving force of large-scale datasets. However, in the realm of 3D vision, while…
Exploring Disentangled and Controllable Human Image Synthesis: From End-to-End to Stage-by-Stage
Zhengwentai Sun, Chenghong Li, Hongjie Liao +7
Achieving fine-grained controllability in human image synthesis is a long-standing challenge in computer vision. Existing methods primarily focus on either facial synthesis or near…