3 citations · 4 across the 7 of their papers we have counts for
9 papers
AIMold: An Autonomous AI-based Pipeline for Complex Mold Design
Pengyun Qiu, Shuo Wang, Zeyuan Chen +3
Injection molding is the cornerstone of mass-producing plastic components. While current algorithms can automate mold design for basic geometries using standard two-piece molds, co…
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…
Omni123: Exploring 3D Native Foundation Models with Limited 3D Data by Unifying Text to 2D and 3D Generation
Chongjie Ye, Cheng Cao, Chuanyu Pan +4
Recent multimodal large language models have achieved strong performance in unified text and image understanding and generation, yet extending such native capability to 3D remains…
ReconViaGen: Towards Accurate Multi-view 3D Object Reconstruction via Generation
Jiahao Chang, Chongjie Ye, Yushuang Wu +6
Existing multi-view 3D object reconstruction methods heavily rely on sufficient overlap between input views, where occlusions and sparse coverage in practice frequently yield sever…
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…
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…
MAG: Multi-Modal Aligned Autoregressive Co-Speech Gesture Generation without Vector Quantization
Binjie Liu, Lina Liu, Sanyi Zhang +5
This work focuses on full-body co-speech gesture generation. Existing methods typically employ an autoregressive model accompanied by vector-quantized tokens for gesture generation…
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…
GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond
Chongjie Ye, Yinyu Nie, Jiahao Chang +3
We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implem…