https://github.com/raotnameh/AML_Course/tree/main/project
Generalized Product Quantization Network for Semi-supervised Image Retrieval
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 56
- 보존된 평가 기록
- 372
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/reedscot/cvpr2016
Learning Deep Representations of Fine-grained Visual Descriptions
https://github.com/rightlit/StackGAN-v2-rev
Learning Deep Representations of Fine-grained Visual Descriptions
https://github.com/rmokady/clip_prefix_caption
Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
https://github.com/roboflow/rf-detr
https://github.com/rohitbhaskar/online-ads-repository
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
https://github.com/ronghanghu/natural-language-object-retrieval
https://github.com/roudimit/AVLnet
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
https://github.com/rui-yan/CS229-final-project
https://github.com/ryankiros/visual-semantic-embedding
Multimodal Convolutional Neural Networks for Matching Image and Sentence
https://github.com/sagachat/VLASE
https://github.com/saibr/iovpr
Self-supervising Fine-grained Region Similarities for Large-scale Image Localization
https://github.com/salanueva/UniVSE
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
https://github.com/samaonline/3D-Shape-Reconstruction-from-Free-Hand-Sketches
https://github.com/satwikkottur/VisualWord2Vec
Visual Word2Vec (vis-w2v): Learning Visually Grounded Word Embeddings Using Abstract Scenes
https://github.com/sbunian/VINS
https://github.com/seatizendoi/dinovdeau
https://github.com/sebastianpinedaar/machine-learning-codes/blob/master/metric-learning/SoftTripleLoss.ipynb
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
https://github.com/serengil/cipherface
https://github.com/serengil/deepface
https://github.com/serengil/lightphe
https://github.com/shmsw25/factscore
https://github.com/shubham-gupta-iitr/mmmlX
https://github.com/sithu31296/simple-object-tracking
https://github.com/skunkworksai/bakllava
https://github.com/social-ai-studio/matk
https://github.com/soco-ai/SF-QA
https://github.com/sounakdey/doodle2search
Doodle to Search: Practical Zero-Shot Sketch-based Image Retrieval
https://github.com/souvikshanku/digit-captioning
Deep Visual-Semantic Alignments for Generating Image Descriptions
https://github.com/ssharoff/cognates
Improving zero-shot learning by mitigating the hubness problem
https://github.com/sshh12/multi_token
https://github.com/stschubert/vpr_tutorial
Rethinking Visual Geo-localization for Large-Scale Applications
https://github.com/sunil-rival/insightface
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/sunsmarterjie/chatterbox
https://github.com/surajiyer/Recommender-Systems
https://github.com/suruoxi/DistanceWeightedSampling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.