4 citations · 5 across the 8 of their papers we have counts for
10 papers
PixelDiT2: Representation-Grounded Pixel Diffusion Transformers
Yongsheng Yu, Wei Xiong, Yichen Sheng +2
Recent advances in pixel-space diffusion models have narrowed the image quality gap with latent-space diffusion, but still converge more slowly and lag behind in final image qualit…
VideoArgus: Agentic Rubric-Grounded Unified Evaluation for Video Generation and Editing
Ziyun Zeng, Zixuan Wang, Yongsheng Yu +2
Evaluating generated videos remains challenging because existing benchmarks rely on fixed evaluation content, cover only a subset of generation and editing settings, and provide li…
Aurora: Unified Video Editing with a Tool-Using Agent
Yongsheng Yu, Ziyun Zeng, Zhiyuan Xiao +4
Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and reference images, and one set o…
PixPerfect: Seamless Latent Diffusion Local Editing with Discriminative Pixel-Space Refinement
Haitian Zheng, Yuan Yao, Yongsheng Yu +3
Latent Diffusion Models (LDMs) have markedly advanced the quality of image inpainting and local editing. However, the inherent latent compression often introduces pixel-level incon…
PixelDiT: Pixel Diffusion Transformers for Image Generation
Yongsheng Yu, Wei Xiong, Weili Nie +3
Latent-space modeling has been the standard for Diffusion Transformers (DiTs). However, it relies on a two-stage pipeline where the pretrained autoencoder introduces lossy reconstr…
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration
Yongsheng Yu, Haitian Zheng, Zhifei Zhang +7
Recent progress in generative models has significantly improved image restoration capabilities, particularly through powerful diffusion models that offer remarkable recovery of sem…
OmniPaint: Mastering Object-Oriented Editing via Disentangled Insertion-Removal Inpainting
Yongsheng Yu, Ziyun Zeng, Haitian Zheng +1
Diffusion-based generative models have revolutionized object-oriented image editing, yet their deployment in realistic object removal and insertion remains hampered by challenges s…
Chain-of-Thought Prompting for Demographic Inference with Large Multimodal Models
Yongsheng Yu, Jiebo Luo
Conventional demographic inference methods have predominantly operated under the supervision of accurately labeled data, yet struggle to adapt to shifting social landscapes and div…
PromptFix: You Prompt and We Fix the Photo
Yongsheng Yu, Ziyun Zeng, Hang Hua +2
Diffusion models equipped with language models demonstrate excellent controllability in image generation tasks, allowing image processing to adhere to human instructions. However,…
GPT-4V(ision) as A Social Media Analysis Engine
Hanjia Lyu, Jinfa Huang, Daoan Zhang +6
Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest i…