32 citations · 50 across the 9 of their papers we have counts for
10 papers · 1 filter
Qwen-Image-PE: Learning Visual Design for Text-to-Image Prompt Enhancement
Zekai Zhang, Yanran Zhang, Shengming Yin +26
Learning visual design is essential for prompt enhancement (PE) to turn underspecified user requests into coherent visual specifications for text-to-image (T2I) generation. Existin…
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-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…
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…
Geometry Reinforced Efficient Attention Tuning Equipped with Normals for Robust Stereo Matching
Jiahao Li, Xinhong Chen, Zhengmin Jiang +3
Despite remarkable advances in image-driven stereo matching over the past decade, Synthetic-to-Realistic ZeroShot (Syn-to-Real) generalization remains an open challenge. This subop…
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
Desai Xie, Jiahao Li, Hao Tan +6
Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, d…
Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model
Jiahao Li, Hao Tan, Kai Zhang +7
Text-to-3D with diffusion models has achieved remarkable progress in recent years. However, existing methods either rely on score distillation-based optimization which suffer from…
DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan +8
We propose \textbf{DMV3D}, a novel 3D generation approach that uses a transformer-based 3D large reconstruction model to denoise multi-view diffusion. Our reconstruction model inco…