collaborators

7 papers

cs.CV2026

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

Yong Liu, Xiaolong Fu, Zihang Xu +10

We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for t…

cs.CV2026

GMO-EDIT: Grounded Multi-Operation Editing for E-Commerce Images

Zipeng Guo, Xiaoan Liu, Lichen Ma +9

Real-world e-commerce image editing often requires multiple, localized, and auditable operations rather than global restyling. This compositional nature poses a dual challenge: mod…

cs.CV2026

PixelU: A U-Shaped Transformer for Efficient End-to-End Pixel Diffusion

Zipeng Guo, Lichen Ma, Yu He +4

End-to-end pixel-space diffusion models bypass the lossy compression of Latent Diffusion Models (LDMs) but struggle to jointly model low-frequency semantics and high-frequency sign…

cs.CV2026

Dynamic-TreeRPO: Breaking the Independent Trajectory Bottleneck with Structured Sampling

Xiaolong Fu, Lichen Ma, Zipeng Guo +9

The integration of Reinforcement Learning (RL) into flow matching models for text-to-image (T2I) generation has driven substantial advances in generation quality. However, these ga…

cs.CV2026

UM-Text: A Unified Multimodal Model for Image Understanding and Visual Text Editing

Lichen Ma, Xiaolong Fu, Gaojing Zhou +6

With the rapid advancement of image generation, visual text editing using natural language instructions has received increasing attention. The main challenge of this task is to ful…

cs.LG2026

Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models

Lit Sin Tan, Junzhe Chen, Xiaolong Fu +5

Existing test-time scaling (TTS) methods for unified multimodal models (UMMs) in text-to-image (T2I) generation primarily rely on search or sampling strategies that produce only in…