127 citations · 481 across the 22 of their papers we have counts for
22 papers
Digging Into Normal Incorporated Stereo Matching
Zihua Liu, Songyan Zhang, Zhicheng Wang +1
Despite the remarkable progress facilitated by learning-based stereo-matching algorithms, disparity estimation in low-texture, occluded, and bordered regions still remains a bottle…
Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Counting
Zhicheng Wang, Liwen Xiao, Zhiguo Cao +1
Class-agnostic counting (CAC) aims to count objects of interest from a query image given few exemplars. This task is typically addressed by extracting the features of query image a…
Reconstruction-Aware Prior Distillation for Semi-supervised Point Cloud Completion
Zhaoxin Fan, Yulin He, Zhicheng Wang +3
Real-world sensors often produce incomplete, irregular, and noisy point clouds, making point cloud completion increasingly important. However, most existing completion methods rely…
Object Level Depth Reconstruction for Category Level 6D Object Pose Estimation From Monocular RGB Image
Zhaoxin Fan, Zhenbo Song, Jian Xu +4
Recently, RGBD-based category-level 6D object pose estimation has achieved promising improvement in performance, however, the requirement of depth information prohibits broader app…
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware Association
Sen Yang, Zhicheng Wang, Ze Chen +7
This paper presents a new method to solve keypoint detection and instance association by using Transformer. For bottom-up multi-person pose estimation models, they need to detect k…
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation
Zhaoxin Fan, Zhengbo Song, Jian Xu +4
Recently, category-level 6D object pose estimation has achieved significant improvements with the development of reconstructing canonical 3D representations. However, the reconstru…
Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads
Xiaohu Jiang, Ze Chen, Zhicheng Wang +2
After DETR was proposed, this novel transformer-based detection paradigm which performs several cross-attentions between object queries and feature maps for predictions has subsequ…
Adaptive Dilated Convolution For Human Pose Estimation
Zhengxiong Luo, Zhicheng Wang, Yan Huang +3
Most existing human pose estimation (HPE) methods exploit multi-scale information by fusing feature maps of four different spatial sizes, \ie , , , and of th…
SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation
Yanjie Li, Sen Yang, Peidong Liu +5
The 2D heatmap-based approaches have dominated Human Pose Estimation (HPE) for years due to high performance. However, the long-standing quantization error problem in the 2D heatma…
Graph-MLP: Node Classification without Message Passing in Graph
Yang Hu, Haoxuan You, Zhecan Wang +3
Graph Neural Network (GNN) has been demonstrated its effectiveness in dealing with non-Euclidean structural data. Both spatial-based and spectral-based GNNs are relying on adjacenc…
DAVOS: Semi-Supervised Video Object Segmentation via Adversarial Domain Adaptation
Jinshuo Zhang, Zhicheng Wang, Songyan Zhang +1
Domain shift has always been one of the primary issues in video object segmentation (VOS), for which models suffer from degeneration when tested on unfamiliar datasets. Recently, m…
General Instance Distillation for Object Detection
Xing Dai, Zeren Jiang, Zhao Wu +4
In recent years, knowledge distillation has been proved to be an effective solution for model compression. This approach can make lightweight student models acquire the knowledge e…
V2F-Net: Explicit Decomposition of Occluded Pedestrian Detection
Mingyang Shang, Dawei Xiang, Zhicheng Wang +1
Occlusion is very challenging in pedestrian detection. In this paper, we propose a simple yet effective method named V2F-Net, which explicitly decomposes occluded pedestrian detect…
TokenPose: Learning Keypoint Tokens for Human Pose Estimation
Yanjie Li, Shoukui Zhang, Zhicheng Wang +4
Human pose estimation deeply relies on visual clues and anatomical constraints between parts to locate keypoints. Most existing CNN-based methods do well in visual representation,…
IBRNet: Learning Multi-View Image-Based Rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova +6
We present a method that synthesizes novel views of complex scenes by interpolating a sparse set of nearby views. The core of our method is a network architecture that includes a m…
Efficient Human Pose Estimation by Learning Deeply Aggregated Representations
Zhengxiong Luo, Zhicheng Wang, Yuanhao Cai +6
In this paper, we propose an efficient human pose estimation network (DANet) by learning deeply aggregated representations. Most existing models explore multi-scale information mai…
Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation
Zhengxiong Luo, Zhicheng Wang, Yan Huang +2
Heatmap regression has become the most prevalent choice for nowadays human pose estimation methods. The ground-truth heatmaps are usually constructed via covering all skeletal keyp…
EDNet: Efficient Disparity Estimation with Cost Volume Combination and Attention-based Spatial Residual
Songyan Zhang, Zhicheng Wang, Qiang Wang +3
Existing state-of-the-art disparity estimation works mostly leverage the 4D concatenation volume and construct a very deep 3D convolution neural network (CNN) for disparity regress…
High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification
Guan'an Wang, Shuo Yang, Huanyu Liu +6
Occluded person re-identification (ReID) aims to match occluded person images to holistic ones across dis-joint cameras. In this paper, we propose a novel framework by learning hig…
Learning Delicate Local Representations for Multi-Person Pose Estimation
Yuanhao Cai, Zhicheng Wang, Zhengxiong Luo +7
In this paper, we propose a novel method called Residual Steps Network (RSN). RSN aggregates features with the same spatial size (Intra-level features) efficiently to obtain delica…
Rethinking on Multi-Stage Networks for Human Pose Estimation
Wenbo Li, Zhicheng Wang, Binyi Yin +7
Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods. While multi-stage methods are seemingly more suited for the task, their performa…
Cascaded Pyramid Network for Multi-Person Pose Estimation
Yilun Chen, Zhicheng Wang, Yuxiang Peng +3
The topic of multi-person pose estimation has been largely improved recently, especially with the development of convolutional neural network. However, there still exist a lot of c…