collaborators

9 papers

cs.AI2026

Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models

Wenxiao Fan, Jingling Fu, Lichen Ma +6

Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences with local objectives. This ove…

cs.CV2026

iFAN: Inference-Aware Learning for Plain Mask Transformers

Fang Li, Yu He, Haoyang Tong +7

Query-based mask transformers assemble segmentation outputs through pixel-wise competition among query predictions of the final layer, yet this inference process is not explicitly…

cs.CV2026

Match One, Learn with Graph: One-to-Graph Query Collaboration with Backward Sharing for Object Detection

Wenxiao Fan, Jingling Fu, Luohang Liu +8

One-to-one (O2O) matching enables Detection Transformers (DETRs) to perform end-to-end set prediction by assigning each object to a single positive query. However, the strongest cl…

cs.CV2026

Recompute or Reuse? Diagnosing and Mitigating Textual Shortcuts in VLM Self-Reflection

Wenxiao Fan, Jingling Fu, Fang Li +9

Vision-language models (VLMs) are expected to revise their reasoning when visual evidence changes. Failures to do so are often attributed to insufficient visual attention or contex…

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

LiWi: Layering in the Wild

Yu He, Fang Li, Haoyang Tong +7

Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains. The layering of in-the-wil…

cs.CV2026

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion

Lichen Ma, Zipeng Guo, Yu He +5

To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged as a compelling end-to-end pa…

cs.CV2025

NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results

Xiaohong Liu, Xiongkuo Min, Qiang Hu +92

This paper reports on the NTIRE 2025 XGC Quality Assessment Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) a…

cs.CV2025

NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment

Shuhao Han, Haotian Fan, Fangyuan Kong +112

This paper reports on the NTIRE 2025 challenge on Text to Image (T2I) generation model quality assessment, which will be held in conjunction with the New Trends in Image Restoratio…