1 citations · 2 across the 9 of their papers we have counts for
11 papers
Image Diffusion Models Are Good 3D Human Motion Generators
Siyuan Yang, Chong Wang, Hao Cheng +4
Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different joint layouts. We investigate…
Persistence Forcing: Exploiting Feature Specialization in Pixel-Space Diffusion
Chong Wang, Zixuan Fu, Shiqi Huang +3
Pixel-space diffusion Transformers (DiTs) directly operate on high-dimensional visual data, yet their hidden representations typically undergo uniform refinement across depth. Natu…
A Frozen Pixel-Space Diffusion Model Can Guide Itself with Its Own Samples
Zixuan Fu, Chong Wang, Lanqing Guo +3
Pixel-space diffusion models aim to learn an end-to-end generator directly over raw pixels. This is challenging because a single model must capture both global structure and local…
Improving Flexible Image Tokenizers for Autoregressive Image Generation
Zixuan Fu, Lanqing Guo, Chong Wang +3
Flexible image tokenizers aim to represent an image using an ordered 1D variable-length token sequence. This flexible tokenization is typically achieved through nested dropout, whe…
Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual
Chong Wang, Lanqing Guo, Zixuan Fu +4
Plug-and-play (PnP) methods offer an iterative strategy for solving image restoration (IR) problems in a zero-shot manner, using a learned \textit{discriminative denoiser} as the i…
Temporal As a Plugin: Unsupervised Video Denoising with Pre-Trained Image Denoisers
Zixuan Fu, Lanqing Guo, Chong Wang +3
Recent advancements in deep learning have shown impressive results in image and video denoising, leveraging extensive pairs of noisy and noise-free data for supervision. However, t…
SoftShadow: Leveraging Soft Masks for Penumbra-Aware Shadow Removal
Xinrui Wang, Lanqing Guo, Xiyu Wang +2
Recent advancements in deep learning have yielded promising results for the image shadow removal task. However, most existing methods rely on binary pre-generated shadow masks. The…
ContextGS: Compact 3D Gaussian Splatting with Anchor Level Context Model
Yufei Wang, Zhihao Li, Lanqing Guo +3
Recently, 3D Gaussian Splatting (3DGS) has become a promising framework for novel view synthesis, offering fast rendering speeds and high fidelity. However, the large number of Gau…
Benchmarking Adversarial Robustness of Image Shadow Removal with Shadow-adaptive Attacks
Chong Wang, Yi Yu, Lanqing Guo +1
Shadow removal is a task aimed at erasing regional shadows present in images and reinstating visually pleasing natural scenes with consistent illumination. While recent deep learni…
Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI
Chong Wang, Lanqing Guo, Yufei Wang +3
Deep unfolding networks (DUN) have emerged as a popular iterative framework for accelerated magnetic resonance imaging (MRI) reconstruction. However, conventional DUN aims to recon…
Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation
Lanqing Guo, Yingqing He, Haoxin Chen +9
Diffusion models have proven to be highly effective in image and video generation; however, they encounter challenges in the correct composition of objects when generating images o…