9 papers · 1 filter
MixDiffusion: Mixing Diffusion-based Uni-condition Text-to-Image Generation Models for Multi-condition Image Synthesis
Pengcheng Wan, Liang Han, Lin Xu +2
Recent advances in text-to-image (T2I) generation have enabled controllable image synthesis by incorporating conditions beyond text. However, most existing diffusion-based methods…
City-Level 3D Surface Reconstruction with Viewpoint Orientation Partitioning and Scene Completion
Liang Han, Wenyuan Zhang, Junsheng Zhou +2
Multi-view 3D surface reconstruction is a longstanding challenge in computer vision. Although recent large-scale reconstruction methods based on 3D Gaussian Splatting (3DGS) achiev…
Sparse-View Surface Reconstruction using Gaussian Splatting through High-Confidence Depth Propagation with Normal Priors
Liang Han, Bangcai Wei, Junsheng Zhou +2
3D reconstruction from sparse views is a challenging task in 3D computer vision. Recent studies on 3D Gaussian Splatting (3DGS) have achieved remarkable results with sparse views i…
FREPix: Frequency-Heterogeneous Flow Matching for Pixel-Space Image Generation
Mingfeng Lin, Jiakun Chen, Liang Han +1
Pixel-space diffusion has re-emerged as a promising alternative to latent-space generation because it avoids the representation bottleneck introduced by VAEs. Yet most existing met…
4C4D: 4 Camera 4D Gaussian Splatting
Junsheng Zhou, Zhifan Yang, Liang Han +4
This paper tackles the challenge of recovering 4D dynamic scenes from videos captured by as few as four portable cameras. Learning to model scene dynamics for temporally consistent…
SparseRecon: Neural Implicit Surface Reconstruction from Sparse Views with Feature and Depth Consistencies
Liang Han, Xu Zhang, Haichuan Song +3
Surface reconstruction from sparse views aims to reconstruct a 3D shape or scene from few RGB images. The latest methods are either generalization-based or overfitting-based. Howev…
CountDiffusion: Text-to-Image Synthesis with Training-Free Counting-Guidance Diffusion
Yanyu Li, Pencheng Wan, Liang Han +3
Stable Diffusion has advanced text-to-image synthesis, but training models to generate images with accurate object quantity is still difficult due to the high computational cost an…
MonoInstance: Enhancing Monocular Priors via Multi-view Instance Alignment for Neural Rendering and Reconstruction
Wenyuan Zhang, Yixiao Yang, Han Huang +4
Monocular depth priors have been widely adopted by neural rendering in multi-view based tasks such as 3D reconstruction and novel view synthesis. However, due to the inconsistent p…
Binocular-Guided 3D Gaussian Splatting with View Consistency for Sparse View Synthesis
Liang Han, Junsheng Zhou, Yu-Shen Liu +1
Novel view synthesis from sparse inputs is a vital yet challenging task in 3D computer vision. Previous methods explore 3D Gaussian Splatting with neural priors (e.g. depth priors)…