activity
20212024
most citedPAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

5 citations · 11 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2024

Drone-assisted Road Gaussian Splatting with Cross-view Uncertainty

Saining Zhang, Baijun Ye, Xiaoxue Chen +5

Robust and realistic rendering for large-scale road scenes is essential in autonomous driving simulation. Recently, 3D Gaussian Splatting (3D-GS) has made groundbreaking progress i…

cs.CV2024

MonoOcc: Digging into Monocular Semantic Occupancy Prediction

Yupeng Zheng, Xiang Li, Pengfei Li +6

Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and semantic information of scenes from only 2D images. It has garnered significant attention, partic…

cs.CV20241 cited

Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic Dataset and New Metrics

Beiwen Tian, Huan-ang Gao, Leiyao Cui +6

In the past several years, road anomaly segmentation is actively explored in the academia and drawing growing attention in the industry. The rationale behind is straightforward: if…

cs.CV20235 cited

PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

Qiang Zhou, Weize Li, Lihan Jiang +4

Object anomaly detection is an important problem in the field of machine vision and has seen remarkable progress recently. However, two significant challenges hinder its research a…

cs.CV2023

3D Implicit Transporter for Temporally Consistent Keypoint Discovery

Chengliang Zhong, Yuhang Zheng, Yupeng Zheng +9

Keypoint-based representation has proven advantageous in various visual and robotic tasks. However, the existing 2D and 3D methods for detecting keypoints mainly rely on geometric…

cs.CV20231 cited

Car-Studio: Learning Car Radiance Fields from Single-View and Endless In-the-wild Images

Tianyu Liu, Hao Zhao, Yang Yu +2

Compositional neural scene graph studies have shown that radiance fields can be an efficient tool in an editable autonomous driving simulator. However, previous studies learned wit…