most citedGaussianStego: A Generalizable Stenography Pipeline for Generative 3D Gaussians Splatting

7 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

IR3D-Bench: Evaluating Vision-Language Model Scene Understanding as Agentic Inverse Rendering

Parker Liu, Chenxin Li, Zhengxin Li +7

Vision-language models (VLMs) excel at descriptive tasks, but whether they truly understand scenes from visual observations remains uncertain. We introduce IR3D-Bench, a benchmark…

cs.CV2025

Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline

Yuzhi Huang, Chenxin Li, Haitao Zhang +9

Video anomaly detection (VAD) is crucial in scenarios such as surveillance and autonomous driving, where timely detection of unexpected activities is essential. Although existing m…

cs.GR2025

VoxDet: Rethinking 3D Semantic Occupancy Prediction as Dense Object Detection

Wuyang Li, Zhu Yu, Alexandre Alahi

3D semantic occupancy prediction aims to reconstruct the 3D geometry and semantics of the surrounding environment. With dense voxel labels, prior works typically formulate it as a…

cs.CV2024

Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment

Yuanfan Zheng, Jinlin Wu, Wuyang Li +1

Domain Adaptive Object Detection (DAOD) transfers knowledge from a labeled source domain to an unannotated target domain under closed-set assumption. Universal DAOD (UniDAOD) exten…

eess.IV20241 cited

DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation

Xinyu Liu, Wuyang Li, Yixuan Yuan

Semi-supervised medical image segmentation aims to leverage limited annotated data and rich unlabeled data to perform accurate segmentation. However, existing semi-supervised metho…

cs.CV20247 cited

GaussianStego: A Generalizable Stenography Pipeline for Generative 3D Gaussians Splatting

Chenxin Li, Hengyu Liu, Zhiwen Fan +4

Recent advancements in large generative models and real-time neural rendering using point-based techniques pave the way for a future of widespread visual data distribution through…