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cs.CV2026

DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation

Qian Wang, Zhenyu Li, Abdelrahman Eldesokey +1

Subject-driven image generation faces an "Identity-Diversity Paradox", where strong identity preservation often leads to rigid and low-diversity outputs. We propose a post-training…

cs.CV2026

RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection

Tianyu Wang, Zhiyuan Ma, Qian Wang +3

Recent advancements in image generation have achieved impressive results in producing high-quality images. However, existing image generation models still generally struggle with a…

cs.CV20239 cited

InstructEdit: Improving Automatic Masks for Diffusion-based Image Editing With User Instructions

Qian Wang, Biao Zhang, Michael Birsak +1

Recent works have explored text-guided image editing using diffusion models and generated edited images based on text prompts. However, the models struggle to accurately locate the…

cs.CV20233 cited

MDP: A Generalized Framework for Text-Guided Image Editing by Manipulating the Diffusion Path

Qian Wang, Biao Zhang, Michael Birsak +1

Image generation using diffusion can be controlled in multiple ways. In this paper, we systematically analyze the equations of modern generative diffusion networks to propose a fra…

cs.CV2023

BlobGAN-3D: A Spatially-Disentangled 3D-Aware Generative Model for Indoor Scenes

Qian Wang, Yiqun Wang, Michael Birsak +1

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images…