activity
20242026
most citedQwen3-VL Technical Report

14 citations · 29 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV20261 cited

SimAC: A Simple Anti-Customization Method for Protecting Face Privacy against Text-to-Image Synthesis of Diffusion Models

Feifei Wang, Zhentao Tan, Tianyi Wei +2

Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques from both privacy and political…

cs.CV2026

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning

Penghui Yang, Long Xing, Xiaoyi Dong +10

Image and video captioning are fundamental tasks that bridge the visual and linguistic domains, playing a critical role in pre-training Large Vision-Language Models (LVLMs). Curren…

cs.CV202514 cited

Qwen3-VL Technical Report

Shuai Bai, Yuxuan Cai, Ruizhe Chen +61

We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…

cs.CV2025

CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning

Long Xing, Xiaoyi Dong, Yuhang Zang +6

Image captioning is a fundamental task that bridges the visual and linguistic domains, playing a critical role in pre-training Large Vision-Language Models (LVLMs). Current state-o…

cs.CV2025

ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing

Long Xing, Qidong Huang, Xiaoyi Dong +10

This paper presents ScaleCap, an inference-time scalable image captioning strategy that generates comprehensive and detailed image captions. The key challenges of high-quality imag…

cs.CV2025

Light-A-Video: Training-free Video Relighting via Progressive Light Fusion

Yujie Zhou, Jiazi Bu, Pengyang Ling +10

Recent advancements in image relighting models, driven by large-scale datasets and pre-trained diffusion models, have enabled the imposition of consistent lighting. However, video…