Papers with Code 아카이브
Image Retrieval
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Image Retrieval is a fundamental and long-standing computer vision task that involves finding images similar to a given query from a large database. It is often considered a form of fine-grained, instance-level classification. The task is integral to image recognition alongside classification and cross-modal retrieval. By leveraging visual similarity and other criteria, image retrieval enables users to efficiently discover relevant images, making it a crucial tool in applications such as search and recommendation.
Extending CLIP for Category-to-image Retrieval in E-commerce
<span style="color:grey; opacity: 0.6">( Image credit: DELF )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/talal579/Deep-image-matching
https://github.com/tamerthamoqa/facenet-pytorch-glint360k
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/tanyakoh/CBIR
https://github.com/technicolor-research/sodeep
https://github.com/tencentarc/opencompatible
Privacy-Preserving Model Upgrades with Bidirectional Compatible Training in Image Retrieval
https://github.com/tensorflow/models/tree/master/research/delf
Deep Image Retrieval: Learning global representations for image search
https://github.com/tensorflow/neural-structured-learning
https://github.com/thudm/visualglm-6b
https://github.com/thulab/DeepHash
https://github.com/tiger-ai-lab/visualwebinstruct
VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search
https://github.com/tjddus9597/Beyond-Binary-Supervision-CVPR19
https://github.com/tomp11/metric_learning
https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification
https://github.com/ttt496/vit-pytorch
https://github.com/tuananh1007/CNN-Image-Retrieval-in-PyTorch
CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples
https://github.com/uditsharma29/flynet-cann
A Hybrid Compact Neural Architecture for Visual Place Recognition
https://github.com/unispac/visual-adversarial-examples-jailbreak-large-language-models
https://github.com/unsuthee/VariationalDeepSemanticHashing
https://github.com/uzh-rpg/netvlad_tf_open
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/valdecy/pybibx
https://github.com/valeoai/LOST
https://github.com/valeoai/found
https://github.com/vearch/vearch
The Design and Implementation of a Real Time Visual Search System on JD E-commerce Platform
https://github.com/vinnik-dmitry07/PlaceRecognition
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/vl2g/CSTBIR
Composite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex Interactions
https://github.com/vmurahari3/visdial-bert
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/vturrisi/solo-learn
https://github.com/waiyulam/ORCNN
Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation
https://github.com/wglab/gestaltmml
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
https://github.com/wglab/gestaltmml-gestaltgpt
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
https://github.com/whut-yirong/espt
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
https://github.com/wickstrom/relax
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
https://github.com/woctezuma/steam-DINO
https://github.com/woodfrog/vse_infty
https://github.com/wujpbb7/caffe_circleloss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.