1 citations · 1 across the 7 of their papers we have counts for
7 papers
Cyc3D: Fine-grained Controllable 3D Generation via Cycle Consistency Regularization
Hongbin Xu, Chaohui Yu, Feng Xiao +5
Despite the remarkable progress of 3D generation, achieving controllability, i.e., ensuring consistency between generated 3D content and input conditions like edge and depth, remai…
4DStyleGaussian: Zero-shot 4D Style Transfer with Gaussian Splatting
Wanlin Liang, Hongbin Xu, Weitao Chen +2
3D neural style transfer has gained significant attention for its potential to provide user-friendly stylization with spatial consistency. However, existing 3D style transfer metho…
ControLRM: Fast and Controllable 3D Generation via Large Reconstruction Model
Hongbin Xu, Weitao Chen, Zhipeng Zhou +4
Despite recent advancements in 3D generation methods, achieving controllability still remains a challenging issue. Current approaches utilizing score-distillation sampling are hind…
RobustMVS: Single Domain Generalized Deep Multi-view Stereo
Hongbin Xu, Weitao Chen, Baigui Sun +2
Despite the impressive performance of Multi-view Stereo (MVS) approaches given plenty of training samples, the performance degradation when generalizing to unseen domains has not b…
StyleDyRF: Zero-shot 4D Style Transfer for Dynamic Neural Radiance Fields
Hongbin Xu, Weitao Chen, Feng Xiao +2
4D style transfer aims at transferring arbitrary visual style to the synthesized novel views of a dynamic 4D scene with varying viewpoints and times. Existing efforts on 3D style t…
FaceChain: A Playground for Human-centric Artificial Intelligence Generated Content
Yang Liu, Cheng Yu, Lei Shang +17
Recent advancement in personalized image generation have unveiled the intriguing capability of pre-trained text-to-image models on learning identity information from a collection o…
PointDC:Unsupervised Semantic Segmentation of 3D Point Clouds via Cross-modal Distillation and Super-Voxel Clustering
Zisheng Chen, Hongbin Xu, Weitao Chen +5
Semantic segmentation of point clouds usually requires exhausting efforts of human annotations, hence it attracts wide attention to the challenging topic of learning from unlabeled…