794 citations · 4.3k across the 55 of their papers we have counts for
57 papers
GridFormer: Towards Accurate Table Structure Recognition via Grid Prediction
Pengyuan Lyu, Weihong Ma, Hongyi Wang +5
All tables can be represented as grids. Based on this observation, we propose GridFormer, a novel approach for interpreting unconstrained table structures by predicting the vertex…
Unified Frequency-Assisted Transformer Framework for Detecting and Grounding Multi-Modal Manipulation
Huan Liu, Zichang Tan, Qiang Chen +3
Detecting and grounding multi-modal media manipulation (DGM^4) has become increasingly crucial due to the widespread dissemination of face forgery and text misinformation. In this…
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement
Chengyou Jia, Minnan Luo, Zhuohang Dang +3
Dominant Person Search methods aim to localize and recognize query persons in a unified network, which jointly optimizes two sub-tasks, \ie, pedestrian detection and Re-IDentificat…
Admix: Enhancing the Transferability of Adversarial Attacks
Xiaosen Wang, Xuanran He, Jingdong Wang +1
Deep neural networks are known to be extremely vulnerable to adversarial examples under white-box setting. Moreover, the malicious adversaries crafted on the surrogate (source) mod…
SegFix: Model-Agnostic Boundary Refinement for Segmentation
Yuhui Yuan, Jingyi Xie, Xilin Chen +1
We present a model-agnostic post-processing scheme to improve the boundary quality for the segmentation result that is generated by any existing segmentation model. Motivated by th…
Point-Set Anchors for Object Detection, Instance Segmentation and Pose Estimation
Fangyun Wei, Xiao Sun, Hongyang Li +2
A recent approach for object detection and human pose estimation is to regress bounding boxes or human keypoints from a central point on the object or person. While this center-poi…
Distillation Guided Residual Learning for Binary Convolutional Neural Networks
Jianming Ye, Shiliang Zhang, Jingdong Wang
It is challenging to bridge the performance gap between Binary CNN (BCNN) and Floating point CNN (FCNN). We observe that, this performance gap leads to substantial residuals betwee…
Weakly-Supervised Action Localization by Generative Attention Modeling
Baifeng Shi, Qi Dai, Yadong Mu +1
Weakly-supervised temporal action localization is a problem of learning an action localization model with only video-level action labeling available. The general framework largely…
Cross View Fusion for 3D Human Pose Estimation
Haibo Qiu, Chunyu Wang, Jingdong Wang +2
We present an approach to recover absolute 3D human poses from multi-view images by incorporating multi-view geometric priors in our model. It consists of two separate steps: (1) e…
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
Bowen Cheng, Bin Xiao, Jingdong Wang +3
Bottom-up human pose estimation methods have difficulties in predicting the correct pose for small persons due to challenges in scale variation. In this paper, we present HigherHRN…
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang, Ke Sun, Tianheng Cheng +9
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-…
Interlaced Sparse Self-Attention for Semantic Segmentation
Lang Huang, Yuhui Yuan, Jianyuan Guo +3
In this paper, we present a so-called interlaced sparse self-attention approach to improve the efficiency of the \emph{self-attention} mechanism for semantic segmentation. The main…
MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang +22
We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The to…
Group Re-Identification with Multi-grained Matching and Integration
Weiyao Lin, Yuxi Li, Hao Xiao +5
The task of re-identifying groups of people underdifferent camera views is an important yet less-studied problem.Group re-identification (Re-ID) is a very challenging task sinceit…
High-Resolution Representations for Labeling Pixels and Regions
Ke Sun, Yang Zhao, Borui Jiang +7
High-resolution representation learning plays an essential role in many vision problems, e.g., pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite{…
Structured Knowledge Distillation for Dense Prediction
Yifan Liu, Changyong Shun, Jingdong Wang +1
In this work, we consider transferring the structure information from large networks to compact ones for dense prediction tasks in computer vision. Previous knowledge distillation…
Deep High-Resolution Representation Learning for Human Pose Estimation
Ke Sun, Bin Xiao, Dong Liu +1
This is an official pytorch implementation of Deep High-Resolution Representation Learning for Human Pose Estimation. In this work, we are interested in the human pose estimation p…
Collaborative Quantization for Cross-Modal Similarity Search
Ting Zhang, Jingdong Wang
Cross-modal similarity search is a problem about designing a search system supporting querying across content modalities, e.g., using an image to search for texts or using a text t…
Supervised Quantization for Similarity Search
Xiaojuan Wang, Ting Zhang, Guo-Jun Q +2
In this paper, we address the problem of searching for semantically similar images from a large database. We present a compact coding approach, supervised quantization. Our approac…
Deep Triplet Quantization
Bin Liu, Yue Cao, Mingsheng Long +2
Deep hashing establishes efficient and effective image retrieval by end-to-end learning of deep representations and hash codes from similarity data. We present a compact coding sol…
Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation
Shengze Yu, Xin Wang, Wenwu Zhu +2
Cross-platform recommendation aims to improve recommendation accuracy through associating information from different platforms. Existing cross-platform recommendation approaches as…
Weakly Supervised Dense Event Captioning in Videos
Xuguang Duan, Wenbing Huang, Chuang Gan +3
Dense event captioning aims to detect and describe all events of interest contained in a video. Despite the advanced development in this area, existing methods tackle this task by…
Accelerating Deep Neural Networks with Spatial Bottleneck Modules
Junran Peng, Lingxi Xie, Zhaoxiang Zhang +2
This paper presents an efficient module named spatial bottleneck for accelerating the convolutional layers in deep neural networks. The core idea is to decompose convolution into t…
OCNet: Object Context Network for Scene Parsing
Yuhui Yuan, Lang Huang, Jianyuan Guo +3
In this paper, we address the semantic segmentation task with a new context aggregation scheme named \emph{object context}, which focuses on enhancing the role of object informatio…