https://github.com/2020132075/conmae
공식 코드ConMAE: Contour Guided MAE for Unsupervised Vehicle Re-Identification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Vehicle re-identification is the task of identifying the same vehicle across multiple cameras.
<span style="color:grey; opacity: 0.6">( Image credit: A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
ConMAE: Contour Guided MAE for Unsupervised Vehicle Re-Identification
FastReID: A Pytorch Toolbox for General Instance Re-identification
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones
Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification
A Dual-Path Model With Adaptive Attention For Vehicle Re-Identification
Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
VOC-ReID: Vehicle Re-identification based on Vehicle-Orientation-Camera
Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective
Relation Preserving Triplet Mining for Stabilising the Triplet Loss in Re-identification Systems
Robust Re-Identification by Multiple Views Knowledge Distillation
Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary
Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification in Video Imagery
Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
Multi-Domain Learning and Identity Mining for Vehicle Re-Identification
Heterogeneous Relational Complement for Vehicle Re-identification
A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras
VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification
An Empirical Study of Vehicle Re-Identification on the AI City Challenge
Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification
Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification
Adaptive Aspect Ratios with Patch-Mixup-ViT-based Vehicle ReID
Enhancing Vehicle Re-identification and Matching for Weaving Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.