Summary of Catvton: Concatenation Is All You Need For Virtual Try-on with Diffusion Models, by Zheng Chong et al.
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Modelsby Zheng Chong, Xiao…
CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Modelsby Zheng Chong, Xiao…
GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generationby Jingzhi Gong, Sisi Li, Giordano…
Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Modelby Kun Zhao, Jakub Prokop, Javier Montalt Tordera,…
How to Blend Concepts in Diffusion Modelsby Lorenzo Olearo, Giorgio Longari, Simone Melzi, Alessandro Raganato,…
Training-free Composite Scene Generation for Layout-to-Image Synthesisby Jiaqi Liu, Tao Huang, Chang XuFirst submitted to…
NODER: Image Sequence Regression Based on Neural Ordinary Differential Equationsby Hao Bai, Yi HongFirst submitted…
STAGE: Simplified Text-Attributed Graph Embeddings Using Pre-trained LLMsby Aaron Zolnai-Lucas, Jack Boylan, Chris Hokamp, Parsa…
The Fabrication of Reality and Fantasy: Scene Generation with LLM-Assisted Prompt Interpretationby Yi Yao, Chan-Feng…
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise…
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Mapsby Junseo Park, Hyeryung JangFirst submitted to…