most citedSoccerNet 2022 Challenges Results

37 citations · 73 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2022

Repainting and Imitating Learning for Lane Detection

Yue He, Minyue Jiang, Xiaoqing Ye +5

Current lane detection methods are struggling with the invisibility lane issue caused by heavy shadows, severe road mark degradation, and serious vehicle occlusion. As a result, di…

cs.CV202237 cited

SoccerNet 2022 Challenges Results

Silvio Giancola, Anthony Cioppa, Adrien Deliège +91

The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…

cs.CV202219 cited

Spatial Pruned Sparse Convolution for Efficient 3D Object Detection

Jianhui Liu, Yukang Chen, Xiaoqing Ye +3

3D scenes are dominated by a large number of background points, which is redundant for the detection task that mainly needs to focus on foreground objects. In this paper, we analyz…

cs.CV20222 cited

Rope3D: TheRoadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task

Xiaoqing Ye, Mao Shu, Hanyu Li +5

Concurrent perception datasets for autonomous driving are mainly limited to frontal view with sensors mounted on the vehicle. None of them is designed for the overlooked roadside p…

cs.CV20213 cited

Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network

Zhikang Zou, Xiaoye Qu, Pan Zhou +4

Recent deep networks have convincingly demonstrated high capability in crowd counting, which is a critical task attracting widespread attention due to its various industrial applic…

cs.CV2021

Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting

Qiming Wu, Zhikang Zou, Pan Zhou +3

Crowd counting has drawn much attention due to its importance in safety-critical surveillance systems. Especially, deep neural network (DNN) methods have significantly reduced esti…