collaborators

11 papers

cs.CV2026

InstanceControl: Controllable Complex Image Generation without Instance Labeling

Xiaoyu Liu, Huan Wang, Fan Li +4

Controllable image generation methods, such as ControlNet, have demonstrated a remarkable capacity to introduce visual conditions(e.g., depth maps) to guide image generation. Howev…

cs.CV2026

Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation

Chonghuinan Wang, Zhikai Chen, Chunwei Wang +9

The advancement of generative AI models capable of producing text and image marks a critical step forward in the realm of multimodal intelligence, particularly for tasks involving…

cs.CV2026

ShotCrop: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions

Dehong Kong, Lina Lei, Lingtao Zheng +10

Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots from one scene. In practice…

cs.CV2026

Fast Image Super-Resolution via Consistency Rectified Flow

Jiaqi Xu, Wenbo Li, Haoze Sun +8

Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders thei…

cs.CV2026

HP-Edit: A Human-Preference Post-Training Framework for Image Editing

Fan Li, Chonghuinan Wang, Lina Lei +9

Common image editing tasks typically adopt powerful generative diffusion models as the leading paradigm for real-world content editing. Meanwhile, although reinforcement learning (…

cs.CV2026

PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks

Junxian Li, Kai Liu, Leyang Chen +7

Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their potential in supporting compute…