121 citations · 371 across the 17 of their papers we have counts for
13 papers · 1 filter
Open-Vocabulary Point-Cloud Object Detection without 3D Annotation
Yuheng Lu, Chenfeng Xu, Xiaobao Wei +4
The goal of open-vocabulary detection is to identify novel objects based on arbitrary textual descriptions. In this paper, we address open-vocabulary 3D point-cloud detection by a…
Open-Vocabulary 3D Detection via Image-level Class and Debiased Cross-modal Contrastive Learning
Yuheng Lu, Chenfeng Xu, Xiaobao Wei +4
Current point-cloud detection methods have difficulty detecting the open-vocabulary objects in the real world, due to their limited generalization capability. Moreover, it is extre…
Enhancing and Dissecting Crowd Counting By Synthetic Data
Yi Hou, Chengyang Li, Yuheng Lu +4
In this article, we propose a simulated crowd counting dataset CrowdX, which has a large scale, accurate labeling, parameterized realization, and high fidelity. The experimental re…
BBA-net: A bi-branch attention network for crowd counting
Yi Hou, Chengyang Li, Fan Yang +5
In the field of crowd counting, the current mainstream CNN-based regression methods simply extract the density information of pedestrians without finding the position of each perso…
Correlating Edge, Pose with Parsing
Ziwei Zhang, Chi Su, Liang Zheng +1
According to existing studies, human body edge and pose are two beneficial factors to human parsing. The effectiveness of each of the high-level features (edge and pose) is confirm…
FFA-Net: Feature Fusion Attention Network for Single Image Dehazing
Xu Qin, Zhilin Wang, Yuanchao Bai +2
In this paper, we propose an end-to-end feature fusion at-tention network (FFA-Net) to directly restore the haze-free image. The FFA-Net architecture consists of three key componen…
Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
Yuanchao Bai, Huizhu Jia, Ming Jiang +3
Blind image deblurring is a challenging problem in computer vision, which aims to restore both the blur kernel and the latent sharp image from only a blurry observation. Inspired b…
Attention Driven Person Re-identification
Fan Yang, Ke Yan, Shijian Lu +3
Person re-identification (ReID) is a challenging task due to arbitrary human pose variations, background clutters, etc. It has been studied extensively in recent years, but the mul…
Trajectory Factory: Tracklet Cleaving and Re-connection by Deep Siamese Bi-GRU for Multiple Object Tracking
Cong Ma, Changshui Yang, Fan Yang +4
Multi-Object Tracking (MOT) is a challenging task in the complex scene such as surveillance and autonomous driving. In this paper, we propose a novel tracklet processing method to…
Bayer Demosaicking Using Optimized Mean Curvature over RGB channels
Rui Chen, Huizhu Jia, Xiange Wen +1
Color artifacts of demosaicked images are often found at contours due to interpolation across edges and cross-channel aliasing. To tackle this problem, we propose a novel demosaick…
Learning a collaborative multiscale dictionary based on robust empirical mode decomposition
Rui Chen, Huizhu Jia, Xiaodong Xie +1
Dictionary learning is a challenge topic in many image processing areas. The basic goal is to learn a sparse representation from an overcomplete basis set. Due to combining the adv…
Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising
Rui Chen, Huizhu Jia, Xiaodong Xie +1
In this letter, we propose a novel image denoising method based on correlation preserving sparse coding. Because the instable and unreliable correlations among basis set can limit…
Blind restoration for non-uniform aerial images using non-local Retinex model and shearlet-based higher-order regularization
Rui Chen, Huizhu Jia, Xiaodong Xie +1
Aerial images are often degraded by space-varying motion blur and simultaneous uneven illumination. To recover high-quality aerial image from its non-uniform version, we propose a…