270 citations · 591 across the 48 of their papers we have counts for
8 papers · 1 filter
A Discrepancy Aware Framework for Robust Anomaly Detection
Yuxuan Cai, Dingkang Liang, Dongliang Luo +3
Defect detection is a critical research area in artificial intelligence. Recently, synthetic data-based self-supervised learning has shown great potential on this task. Although ma…
Diffusion-based 3D Object Detection with Random Boxes
Xin Zhou, Jinghua Hou, Tingting Yao +6
3D object detection is an essential task for achieving autonomous driving. Existing anchor-based detection methods rely on empirical heuristics setting of anchors, which makes the…
Visual Information Extraction in the Wild: Practical Dataset and End-to-end Solution
Jianfeng Kuang, Wei Hua, Dingkang Liang +4
Visual information extraction (VIE), which aims to simultaneously perform OCR and information extraction in a unified framework, has drawn increasing attention due to its essential…
SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
Dingyuan Zhang, Dingkang Liang, Hongcheng Yang +4
With the development of large language models, many remarkable linguistic systems like ChatGPT have thrived and achieved astonishing success on many tasks, showing the incredible p…
SOOD: Towards Semi-Supervised Oriented Object Detection
Wei Hua, Dingkang Liang, Jingyu Li +4
Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approache…
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language Model
Dingkang Liang, Jiahao Xie, Zhikang Zou +3
Supervised crowd counting relies heavily on costly manual labeling, which is difficult and expensive, especially in dense scenes. To alleviate the problem, we propose a novel unsup…
Super-Resolution Information Enhancement For Crowd Counting
Jiahao Xie, Wei Xu, Dingkang Liang +5
Crowd counting is a challenging task due to the heavy occlusions, scales, and density variations. Existing methods handle these challenges effectively while ignoring low-resolution…
DDS3D: Dense Pseudo-Labels with Dynamic Threshold for Semi-Supervised 3D Object Detection
Jingyu Li, Zhe Liu, Jinghua Hou +1
In this paper, we present a simple yet effective semi-supervised 3D object detector named DDS3D. Our main contributions have two-fold. On the one hand, different from previous work…