activity
20192026
most citedCOIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

14 citations · 25 across the 15 of their papers we have counts for

collaborators

18 papers

cs.CV2026

IBRSteG: Learning a Generalizable Steganography Framework for 3D Gaussian Splatting

Fanye Kong, Hongyu Xia, Yu Zheng +3

Recent advances in deep learning have notably improved steganographic message hiding. However, designing a generalizable steganographic approach for 3D Gaussian Splatting (3DGS) th…

cs.AI2026

EmergentBridge: Improving Zero-Shot Cross-Modal Transfer in Unified Multimodal Embedding Models

Jincheng Xie, Xingchen Xiao, Runheng Liu +3

Unified multimodal embedding spaces underpin practical applications such as cross-modal retrieval and zero-shot recognition. In many real deployments, however, supervision is avail…

cs.CV2026

UniGenDet: A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection

Yanran Zhang, Wenzhao Zheng, Yifei Li +5

In recent years, significant progress has been made in both image generation and generated image detection. Despite their rapid, yet largely independent, development, these two fie…

cs.CL2026

More Than Sum of Its Parts: Deciphering Intent Shifts in Multimodal Hate Speech Detection

Runze Sun, Yu Zheng, Zexuan Xiong +4

Combating hate speech on social media is critical for securing cyberspace, yet relies heavily on the efficacy of automated detection systems. As content formats evolve, hate speech…

cs.CV2026

Attention at Rest Stays at Rest: Breaking Visual Inertia to Mitigate Relation Hallucinations

Boyang Gong, Yu Zheng, Fanye Kong +2

While multimodal large language models demonstrate strong entity-level perception, faithfully grounding relational interactions between objects remains a persistent challenge. Alth…

cs.CV2026

Structural Graph Probing of Vision-Language Models

Haoyu He, Yue Zhuo, Yu Zheng +1

Vision-language models (VLMs) achieve strong multimodal performance, yet how computation is organized across populations of neurons remains poorly understood. In this work, we stud…

cs.CV2026

Measuring 3D Spatial Geometric Consistency in Dynamic Video Generation

Weijia Dou, Wenzhao Zheng, Weiliang Chen +3

Recent generative models can produce high-fidelity videos, yet they often exhibit 3D spatial geometric inconsistencies. Existing evaluation methods fail to accurately characterize…

cs.CV2025

NeXT-IMDL: Build Benchmark for NeXT-Generation Image Manipulation Detection & Localization

Yifei Li, Haoyuan He, Yu Zheng +5

The accessibility surge and abuse risks of user-friendly image editing models have created an urgent need for generalizable, up-to-date methods for Image Manipulation Detection and…

cs.CV2025★ 1 cited

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning

Yifei Li, Wenzhao Zheng, Yanran Zhang +5

The misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated video detectors. However, most exis…

cs.CV2025

QE: Learning Discrete Distribution Discrepancy-aware Quantization Error for Autoregressive-Generated Image Detection

Yanran Zhang, Bingyao Yu, Yu Zheng +5

The emergence of visual autoregressive (AR) models has revolutionized image generation while presenting new challenges for synthetic image detection. Unlike previous GAN or diffusi…

cs.CV2025

Learning Counterfactually Decoupled Attention for Open-World Model Attribution

Yu Zheng, Boyang Gong, Fanye Kong +6

In this paper, we propose a Counterfactually Decoupled Attention Learning (CDAL) method for open-world model attribution. Existing methods rely on handcrafted design of region part…

cs.CV2025

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Weiliang Chen, Wenzhao Zheng, Yu Zheng +4

The flourishing of video generation technologies has endangered the credibility of real-world information and intensified the demand for AI-generated video detectors. Despite some…

cs.CV2024

OPONeRF: One-Point-One NeRF for Robust Neural Rendering

Yu Zheng, Yueqi Duan, Kangfu Zheng +3

In this paper, we propose a One-Point-One NeRF (OPONeRF) framework for robust scene rendering. Existing NeRFs are designed based on a key assumption that the target scene remains u…

cs.CV2024★ 1 cited

Gaussian-Det: Learning Closed-Surface Gaussians for 3D Object Detection

Hongru Yan, Yu Zheng, Yueqi Duan

Skins wrapping around our bodies, leathers covering over the sofa, sheet metal coating the car - it suggests that objects are enclosed by a series of continuous surfaces, which pro…

cs.CV2023★ 2 cited

Semantic Ray: Learning a Generalizable Semantic Field with Cross-Reprojection Attention

Fangfu Liu, Chubin Zhang, Yu Zheng +1

In this paper, we aim to learn a semantic radiance field from multiple scenes that is accurate, efficient and generalizable. While most existing NeRFs target at the tasks of neural…

cs.CV2022★ 6 cited

HyperDet3D: Learning a Scene-conditioned 3D Object Detector

Yu Zheng, Yueqi Duan, Jiwen Lu +2

A bathtub in a library, a sink in an office, a bed in a laundry room -- the counter-intuition suggests that scene provides important prior knowledge for 3D object detection, which…

cs.CV2022★ 1 cited

Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement

Xiuwei Xu, Yifan Wang, Yu Zheng +3

In this paper, we propose a weakly-supervised approach for 3D object detection, which makes it possible to train a strong 3D detector with position-level annotations (i.e. annotati…

cs.CV2019★ 14 cited

COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysis

Yansong Tang, Dajun Ding, Yongming Rao +5

There are substantial instructional videos on the Internet, which enables us to acquire knowledge for completing various tasks. However, most existing datasets for instructional vi…