1
Joint Bilateral-Resolution Identity Modeling for Cross-Resolution Person Re-Identification
2
Prototype-Guided Saliency Feature Learning for Person Search
3
Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification
4
Generalizable Person Re-identification with Relevance-aware Mixture of Experts
5
Guided Attention in CNNs for Occluded Pedestrian Detection and Re-identification
6
Anchor-Free Person Search
7
Sequential End-to-end Network for Efficient Person Search
8
Diverse Knowledge Distillation for End-to-End Person Search
9
Learning Multi-Attention Context Graph for Group-Based Re-Identification
10
Box Guided Convolution for Pedestrian Detection
11
Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
12
Long-Short Temporal–Spatial Clues Excited Network for Robust Person Re-identification
13
Norm-Aware Embedding for Efficient Person Search and Tracking
14
Instance Guided Proposal Network for Person Search
15
TCTS: A Task-Consistent Two-Stage Framework for Person Search
16
Bi-Directional Interaction Network for Person Search
17
Joint Person Objectness and Repulsion for Person Search
18
Inter-Region Affinity Distillation for Road Marking Segmentation
19
FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking
20
Hierarchical Online Instance Matching for Person Search
21
Revisiting the Sibling Head in Object Detector
22
Person Search by Separated Modeling and A Mask-Guided Two-Stream CNN Model
23
Intra-Camera Supervised Person Re-Identification
24
PyTorch: An Imperative Style, High-Performance Deep Learning Library
25
Pose-Guided Feature Alignment for Occluded Person Re-Identification
26
Few-Shot Image Recognition With Knowledge Transfer
27
Dynamic Anchor Feature Selection for Single-Shot Object Detection
28
FoveaBox: Beyound Anchor-Based Object Detection
29
Re-ID Driven Localization Refinement for Person Search
30
Revisiting Feature Alignment for One-stage Object Detection
31
MMDetection: Open MMLab Detection Toolbox and Benchmark
32
Query-Guided End-To-End Person Search
33
RepPoints: Point Set Representation for Object Detection
34
CenterNet: Keypoint Triplets for Object Detection
36
High-Level Semantic Feature Detection: A New Perspective for Pedestrian Detection
37
Libra R-CNN: Towards Balanced Learning for Object Detection
38
Learning Context Graph for Person Search
39
FCOS: Fully Convolutional One-Stage Object Detection
40
Structured Knowledge Distillation for Semantic Segmentation
41
CamStyle: A Novel Data Augmentation Method for Person Re-Identification
42
Region Proposal by Guided Anchoring
43
Online Model Distillation for Efficient Video Inference
44
Deformable ConvNets V2: More Deformable, Better Results
45
Tattoo Image Search at Scale: Joint Detection and Compact Representation Learning
46
FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification
47
RCAA: Relational Context-Aware Agents for Person Search
48
Learning deep representations by mutual information estimation and maximization
49
CornerNet: Detecting Objects as Paired Keypoints
50
Person Search by Multi-Scale Matching
51
Person Re-identification in Identity Regression Space
52
Pose Transferrable Person Re-identification
53
Fast Open-World Person Re-Identification
54
Mutual Information Neural Estimation
55
Learning Efficient Object Detection Models with Knowledge Distillation
56
Cascade R-CNN: Delving Into High Quality Object Detection
57
Beyond Part Models: Person Retrieval with Refined Part Pooling
58
Person Transfer GAN to Bridge Domain Gap for Person Re-identification
59
Single-Shot Refinement Neural Network for Object Detection
60
Pose-Driven Deep Convolutional Model for Person Re-identification
61
Focal Loss for Dense Object Detection
62
Mimicking Very Efficient Network for Object Detection
63
Neural Person Search Machines
64
IAN: The Individual Aggregation Network for Person Search
65
Beyond Triplet Loss: A Deep Quadruplet Network for Person Re-identification
66
Person Re-Identification by Camera Correlation Aware Feature Augmentation
67
In Defense of the Triplet Loss for Person Re-Identification
68
Deformable Convolutional Networks
69
CityPersons: A Diverse Dataset for Pedestrian Detection
70
YOLO9000: Better, Faster, Stronger
71
Feature Pyramid Networks for Object Detection
72
Learning without Forgetting
73
Person Re-identification in the Wild
74
Joint Detection and Identification Feature Learning for Person Search
75
Person Re-Identification by Discriminative Selection in Video Ranking
76
Deep Residual Learning for Image Recognition
77
SSD: Single Shot MultiBox Detector
78
You Only Look Once: Unified, Real-Time Object Detection
79
An improved deep learning architecture for person re-identification
80
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
81
Distilling the Knowledge in a Neural Network
82
Joint Deep Learning for Pedestrian Detection
83
Equitability, mutual information, and the maximal information coefficient
84
Person re-identification by symmetry-driven accumulation of local features
85
ImageNet: A large-scale hierarchical image database
86
Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features
87
Distinctive Image Features from Scale-Invariant Keypoints
88
Exclusivity-Consistency Regularized Knowledge Distillation for Face Recognition
89
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