Papers with Code 아카이브

Deep Hashing

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/weiweisong415/Demo_AHCL_for_TGRS2022

공식 코드

Asymmetric Hash Code Learning for Remote Sensing Image Retrieval

https://github.com/willard-yuan/hashing-baseline-for-image-retrieval

공식 코드

Deep Hashing with Category Mask for Fast Video Retrieval

https://github.com/xandery-geek/SAAT

공식 코드

Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval

https://github.com/xunguangwang/ProS-GAN

공식 코드

Prototype-supervised Adversarial Network for Targeted Attack of Deep Hashing

https://github.com/xunguangwang/cgat

공식 코드

CgAT: Center-Guided Adversarial Training for Deep Hashing-Based Retrieval

https://github.com/youngkyunjang/deep-hash-distillation

공식 코드

Deep Hash Distillation for Image Retrieval

https://github.com/zsffq999/SCDH

공식 코드

Semantic Cluster Unary Loss for Efficient Deep Hashing

https://github.com/Evgeneus/Graph-Domain-Adaptaion

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/Kso-Ayaka/MS_Paperwithcode/tree/main/Attribute-Aware%20Deep%20Hashing

Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale Fine-Grained Image Retrieval

https://github.com/Vijetha1/WDHT

Weakly Supervised Deep Image Hashing through Tag Embeddings

https://github.com/cisiplab/cisip-fire

One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective

https://github.com/csdongxian/csdongxian

Targeted Attack for Deep Hashing based Retrieval

https://github.com/deepakks1995/DeepHashing

Dual Asymmetric Deep Hashing Learning

https://github.com/deeplearning-wisc/hypo

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/duolu/fmkit

FMHash: Deep Hashing of In-Air-Handwriting for User Identification

https://github.com/facebookresearch/DomainBed

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/facebookresearch/ModelRatatouille

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/khoadoan106/single_loss_quantization

One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching

https://github.com/szubing/uniood

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/thulab/DeepHash

Deep Triplet Quantization

https://github.com/tosmaster/imagevision

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

https://github.com/xch-liu/geom-tex-dg

Deep Hashing Network for Unsupervised Domain Adaptation

https://github.com/yujiapingyu/Deep-Hashing

Feature Learning based Deep Supervised Hashing with Pairwise Labels

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.