27 citations · 47 across the 7 of their papers we have counts for
7 papers
TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without Training
Yuqi Lin, Minghao Chen, Kaipeng Zhang +7
Contrastive Language-Image Pre-training (CLIP) has demonstrated impressive capabilities in open-vocabulary classification. The class token in the image encoder is trained to captur…
Lidar Point Cloud Guided Monocular 3D Object Detection
Liang Peng, Fei Liu, Zhengxu Yu +5
Monocular 3D object detection is a challenging task in the self-driving and computer vision community. As a common practice, most previous works use manually annotated 3D box label…
Suppress-and-Refine Framework for End-to-End 3D Object Detection
Zili Liu, Guodong Xu, Honghui Yang +5
3D object detector based on Hough voting achieves great success and derives many follow-up works. Despite constantly refreshing the detection accuracy, these works suffer from hand…
RESA: Recurrent Feature-Shift Aggregator for Lane Detection
Tu Zheng, Hao Fang, Yi Zhang +4
Lane detection is one of the most important tasks in self-driving. Due to various complex scenarios (e.g., severe occlusion, ambiguous lanes, etc.) and the sparse supervisory signa…
Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds
Guodong Xu, Wenxiao Wang, Zili Liu +4
3D object detection based on point clouds has become more and more popular. Some methods propose localizing 3D objects directly from raw point clouds to avoid information loss. How…
PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module
Liang Xie, Chao Xiang, Zhengxu Yu +4
LIDAR point clouds and RGB-images are both extremely essential for 3D object detection. So many state-of-the-art 3D detection algorithms dedicate in fusing these two types of data…
Improving Semantic Segmentation via Dilated Affinity
Boxi Wu, Shuai Zhao, Wenqing Chu +2
Introducing explicit constraints on the structural predictions has been an effective way to improve the performance of semantic segmentation models. Existing methods are mainly bas…