5 papers
2D Pre-Training for 3D Pose Estimation
Liyao Jiang, Ruichen Chen, Keith G. Mills
Pre-training is a general method that is used in a range of deep learning tasks. By first training a model on one task, and then further training on the downstream task used for fi…
RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment
Liyao Jiang, Ruichen Chen, Chao Gao +1
Recent text-to-image (T2I) diffusion models achieve remarkable realism, yet faithful prompt-image alignment remains challenging, particularly for complex prompts with multiple obje…
Re-ttention: Ultra Sparse Visual Generation via Attention Statistical Reshape
Ruichen Chen, Keith G. Mills, Liyao Jiang +2
Diffusion Transformers (DiT) have become the de-facto model for generating high-quality visual content like videos and images. A huge bottleneck is the attention mechanism where co…
FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting
Liyao Jiang, Negar Hassanpour, Mohammad Salameh +4
Text-to-image (T2I) diffusion models have demonstrated impressive capabilities in generating high-quality images given a text prompt. However, ensuring the prompt-image alignment r…
PixelMan: Consistent Object Editing with Diffusion Models via Pixel Manipulation and Generation
Liyao Jiang, Negar Hassanpour, Mohammad Salameh +4
Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving…