110 citations · 285 across the 58 of their papers we have counts for
38 papers · 1 filter
Rubrics as Visual-Repair Context for Self-Evolving UI-to-Code Generation
Tianyi Xiong, Zhengyuan Yang, Xiaofei Wang +10
Large vision-language models have shown strong progress in UI-to-code generation, yet their test-time self-evolution remains unstable. We first identify a fundamental obstacle, ter…
Qwen-Image-Agent: Bridging the Context Gap in Real-World Image Generation
Zekai Zhang, Jiahao Li, Jie Zhang +18
While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or dependent on up-to-date knowl…
Qwen-Image-2.0-RL Technical Report
Yixian Xu, Kaiyuan Gao, Yuxiang Chen +25
We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual qu…
Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation
Niantong Li, Guangzheng Hu, Weixu Qiao +35
Text-to-Image generation has evolved from basic image synthesis into a frequently used core capability in professional creative workflows, where simple text-image alignment can no…
Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation
Jie Zhang, Xiaoyue Chen, Anzhe Chen +36
We introduce Qwen-RobotWorld, a language-conditioned video world model for embodied intelligence. With natural language as a unified action interface, it predicts physically ground…
Qwen-Image-Flash: Rethinking the Training Recipe for Few-Step Distillation
Tianhe Wu, Kun Yan, Zikai Zhou +23
Few-step distillation has emerged as a critical component in the development of advanced visual generative foundation models, substantially reducing inference overhead while enabli…
Edit-GRPO: A Locality-Preserving Policy Optimization Framework for Image Editing
Shaodong Xu, Zexian Li, Zhendong Wang +5
A fundamental challenge in image editing lies in preserving spatial locality: edits should improve targeted content without inadvertently altering surrounding regions. However, mos…
Beyond Point-Wise Matching: Structural Representation Alignment for Accelerating Diffusion Transformers
Shaodong Xu, Zhendong Wang, Litong Gong +4
Recent advances in Diffusion Transformers (DiTs) demonstrate that aligning noisy latent states with well-trained semantic features-as pioneered by Representation Alignment (REPA)-c…
Qwen-Image-VAE-2.0 Technical Report
Zekai Zhang, Deqing Li, Kuan Cao +27
We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…
Qwen-Image-2.0 Technical Report
Bing Zhao, Chenfei Wu, Deqing Li +72
We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…
SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation
Longtao Jiang, Jianmin Bao, Zhendong Wang +4
Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-scale image generation. We i…
MM-WebAgent: A Hierarchical Multimodal Web Agent for Webpage Generation
Yan Li, Zezi Zeng, Yifan Yang +12
The rapid progress of Artificial Intelligence Generated Content (AIGC) tools enables images, videos, and visualizations to be created on demand for webpage design, offering a flexi…
StepVAR: Structure-Texture Guided Pruning for Visual Autoregressive Models
Keli Liu, Zhendong Wang, Wengang Zhou +1
Visual AutoRegressive (VAR) models based on next-scale prediction enable efficient hierarchical generation, yet the inference cost grows quadratically at high resolutions. We obser…
Analysis of Converged 3D Gaussian Splatting Solutions: Density Effects and Prediction Limit
Zhendong Wang, Cihan Ruan, Jingchuan Xiao +5
We investigate what structure emerges in 3D Gaussian Splatting (3DGS) solutions from standard multi-view optimization. We term these Rendering-Optimal References (RORs) and analyze…
Thinking Like Van Gogh: Structure-Aware Style Transfer via Flow-Guided 3D Gaussian Splatting
Lebin Zhou, Jingchuan Xiao, Zhendong Wang +4
In 1888, Vincent van Gogh wrote, "I am seeking exaggeration in the essential." This principle, amplifying structural form while suppressing photographic detail, lies at the core of…
TechImage-Bench: Rubric-Based Evaluation for Technical Image Generation
Minheng Ni, Zhengyuan Yang, Yaowen Zhang +9
We study technical image generation, where a model must synthesize information-dense, scientifically precise illustrations from detailed descriptions rather than merely produce vis…
ScaleWeaver: Weaving Efficient Controllable T2I Generation with Multi-Scale Reference Attention
Keli Liu, Zhendong Wang, Wengang Zhou +3
Text-to-image generation with visual autoregressive~(VAR) models has recently achieved impressive advances in generation fidelity and inference efficiency. While control mechanisms…
EchoGen: Generating Visual Echoes in Any Scene via Feed-Forward Subject-Driven Auto-Regressive Model
Ruixiao Dong, Zhendong Wang, Keli Liu +5
Subject-driven generation is a critical task in creative AI; yet current state-of-the-art methods present a stark trade-off. They either rely on computationally expensive, per-subj…
EdiVal-Agent: An Object-Centric Framework for Automated, Fine-Grained Evaluation of Multi-Turn Editing
Tianyu Chen, Yasi Zhang, Zhi Zhang +13
Instruction-based image editing has advanced rapidly, yet reliable and interpretable evaluation remains a bottleneck. Current protocols either (i) depend on paired reference images…
Unified Multimodal Models as Auto-Encoders
Zhiyuan Yan, Kaiqing Lin, Zongjian Li +10
Image-to-text (I2T) understanding and text-to-image (T2I) generation are two fundamental, important yet traditionally isolated multimodal tasks. Despite their intrinsic connection,…
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation
Yuxuan Du, Zhendong Wang, Yuhao Luo +4
The rapid emergence of multimodal deepfakes (visual and auditory content are manipulated in concert) undermines the reliability of existing detectors that rely solely on modality-s…
Few-Step Diffusion via Score identity Distillation
Mingyuan Zhou, Yi Gu, Zhendong Wang
Diffusion distillation has emerged as a promising strategy for accelerating text-to-image (T2I) diffusion models by distilling a pretrained score network into a one- or few-step ge…
DesignDiffusion: High-Quality Text-to-Design Image Generation with Diffusion Models
Zhendong Wang, Jianmin Bao, Shuyang Gu +3
In this paper, we present DesignDiffusion, a simple yet effective framework for the novel task of synthesizing design images from textual descriptions. A primary challenge lies in…
SmartEraser: Remove Anything from Images using Masked-Region Guidance
Longtao Jiang, Zhendong Wang, Jianmin Bao +5
Object removal has so far been dominated by the mask-and-inpaint paradigm, where the masked region is excluded from the input, leaving models relying on unmasked areas to inpaint t…