https://github.com/XiSHEN0220/ArtMiner
Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/XiSHEN0220/WatermarkReco
Large-Scale Historical Watermark Recognition: dataset and a new consistency-based approach
https://github.com/XuyangBai/D3Feat
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/YadiraF/DECA
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/ZhangYiqun018/StickerConv
https://github.com/abaldrati/clip4cirdemo
https://github.com/abhidipbhattacharyya/srl_aware_ret
https://github.com/adam-mehdi/MuarAugment
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
https://github.com/adipai/haralick-textural-feature-analysis
Gray Level Co-Occurrence Matrices: Generalisation and Some New Features
https://github.com/adrienangeli/dino
https://github.com/afrazsalim/WebBasedGameWithNodeJs
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/ahangchen/rank-reid
A Discriminatively Learned CNN Embedding for Person Re-identification
https://github.com/ahmedelmahy/myownvit
https://github.com/ahmetius/diffusion-retrieval
Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations
https://github.com/albanie/mcnCrossModalEmotions
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/albertotestoni/ndq_visual_objects
https://github.com/alibaba/EasyCV
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/alibaba/graphtranslator
https://github.com/alinstein/Modify-image-by-text
Composing Text and Image for Image Retrieval - An Empirical Odyssey
https://github.com/allenai/allennlp-models
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/allenai/swig
https://github.com/almazan/deep-image-retrieval
Particular object retrieval with integral max-pooling of CNN activations
https://github.com/anaymehrotra/ranking-with-implicit-bias
Mitigating Bias in Set Selection with Noisy Protected Attributes
https://github.com/aneeshan95/Cross-modal_Hierarchy_FGSBIR
Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval
https://github.com/anguoyuan/Hypergraph-Propagation-and-Community-Selection-for-Objects-Retrieval
https://github.com/anguyen8/deepface-emd
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
https://github.com/anguyen8/face-vit
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
https://github.com/apsdehal/flava-tutorials
https://github.com/arijitray1993/COLA
https://github.com/armandvilalta/Full-network-multimodal-embeddings
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
https://github.com/arraiyopensource/torchgeometry
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
https://github.com/baaivision/eva
https://github.com/babylonhealth/fastText_multilingual
Improving zero-shot learning by mitigating the hubness problem
https://github.com/baldassarreFe/deep-koalarization
CNN Features off-the-shelf: an Astounding Baseline for Recognition
https://github.com/beneroth13/dinov2
https://github.com/beresandras/contrastive-classification-keras
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.