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cs.CV2025
HanDrawer: Leveraging Spatial Information to Render Realistic Hands Using a Conditional Diffusion Model in Single Stage
Qifan Fu, Xu Chen, Muhammad Asad +3
Although diffusion methods excel in text-to-image generation, generating accurate hand gestures remains a major challenge, resulting in severe artifacts, such as incorrect number o…
cs.CV2024
Adaptive Multi-Modal Control of Digital Human Hand Synthesis Using a Region-Aware Cycle Loss
Qifan Fu, Xiaohang Yang, Muhammad Asad +3
Diffusion models have shown their remarkable ability to synthesize images, including the generation of humans in specific poses. However, current models face challenges in adequate…
cs.CV2024
Improving Image De-raining Using Reference-Guided Transformers
Zihao Ye, Jaehoon Cho, Changjae Oh
Image de-raining is a critical task in computer vision to improve visibility and enhance the robustness of outdoor vision systems. While recent advances in de-raining methods have…