activity
20242026
most citedDocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception

2 citations · 3 across the 6 of their papers we have counts for

collaborators

8 papers

cs.AI2026

PosterMELD: Multi-Agent Paper-to-Poster Generation for Controllable Design Diversity with Editable Print-Ready Outputs

Haojie Hu, Chenhao Dang, Yaojia Liu +3

Scientific poster construction compresses a long multimodal paper into a readable, editable canvas. Existing systems hide request-level failures by scoring only completed outputs;…

cs.CV2025

OmniDocLayout: Towards Diverse Document Layout Generation via Coarse-to-Fine LLM Learning

Hengrui Kang, Zhuangcheng Gu, Zhiyuan Zhao +4

Document AI has advanced rapidly and is attracting increasing attention. Yet, while most efforts have focused on document layout analysis (DLA), its generative counterpart, layout…

cs.CV2025

OmniAID: Decoupling Semantics and Artifacts for Universal AI-Generated Image Detection in the Wild

Yuncheng Guo, Junyan Ye, Chenjue Zhang +4

A truly universal AI-Generated Image (AIGI) detector must simultaneously generalize across diverse generative models and varied semantic content. Current methods learn a single, en…

cs.CV2025

Prune2Drive: A Plug-and-Play Framework for Accelerating Vision-Language Models in Autonomous Driving

Minhao Xiong, Zichen Wen, Zhuangcheng Gu +9

Vision-Language Models (VLMs) have emerged as a promising paradigm in autonomous driving (AD), providing a unified framework for perception and decision-making. However, their real…

cs.CV2025

LEGION: Learning to Ground and Explain for Synthetic Image Detection

Hengrui Kang, Siwei Wen, Zichen Wen +8

The rapid advancements in generative technology have emerged as a double-edged sword. While offering powerful tools that enhance convenience, they also pose significant social conc…

cs.CV2025

Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation

Siwei Wen, Junyan Ye, Peilin Feng +7

With the rapid advancement of Artificial Intelligence Generated Content (AIGC) technologies, synthetic images have become increasingly prevalent in everyday life, posing new challe…

cs.CV2024★ 2 cited

DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception

Zhiyuan Zhao, Hengrui Kang, Bin Wang +1

Document Layout Analysis is crucial for real-world document understanding systems, but it encounters a challenging trade-off between speed and accuracy: multimodal methods leveragi…

cs.CV2024★ 1 cited

LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models

Junyan Ye, Baichuan Zhou, Zilong Huang +12

With the rapid development of AI-generated content, the future internet may be inundated with synthetic data, making the discrimination of authentic and credible multimodal data in…