https://github.com/google-research/vmf_embeddings
공식 코드von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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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/goukoutaki/FSDH
공식 코드https://github.com/gr8joo/IIAE
공식 코드Variational Interaction Information Maximization for Cross-domain Disentanglement
https://github.com/gtolias/how
공식 코드Learning and aggregating deep local descriptors for instance-level recognition
https://github.com/gtolias/mom
공식 코드Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations
https://github.com/guoqianyu-alberta/rankdnn
공식 코드https://github.com/haitaowutju/uncertainty-aware-blur-prior
공식 코드Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior
https://github.com/hamid-amiri/mcdl-image-annotation
공식 코드Toward Real-Time Image Annotation Using Marginalized Coupled Dictionary Learning
https://github.com/hansonchen1996/mmgl
공식 코드https://github.com/haokunwen/awesome-composed-image-retrieval
공식 코드https://github.com/haotian-liu/LLaVA
공식 코드https://github.com/haowang1992/DSN
공식 코드Domain-Smoothing Network for Zero-Shot Sketch-Based Image Retrieval
https://github.com/harveyhuang18/emr_merging
공식 코드https://github.com/hawaii-ai/wvnet
공식 코드https://github.com/hly1998/brcd
공식 코드Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing
https://github.com/hly1998/nhl
공식 코드A Flexible Plug-and-Play Module for Generating Variable-Length
https://github.com/hlzz/mirror
공식 코드Matchable Image Retrieval by Learning from Surface Reconstruction
https://github.com/hmchuong/CoLLM
공식 코드https://github.com/hnanhtuan/selectiveConvFeature
공식 코드https://github.com/hsiehjackson/mr.right
공식 코드Mr. Right: Multimodal Retrieval on Representation of ImaGe witH Text
https://github.com/htconquer/BGAN
공식 코드https://github.com/htconquer/ddh
공식 코드https://github.com/htlsn/igan
공식 코드https://github.com/huangzongheng/mathm
공식 코드Modality-Aware Triplet Hard Mining for Zero-shot Sketch-Based Image Retrieval
https://github.com/human-analysis/hers-encrypted-image-search
공식 코드https://github.com/humaticslab/seam-match-rcnn
공식 코드https://github.com/hyounghk/caise
공식 코드https://github.com/iamhankai/attribute-aware-attention
공식 코드Attribute-Aware Attention Model for Fine-grained Representation Learning
https://github.com/iapalm/Spoken-ObjectNet
공식 코드https://github.com/ibm/remote-sensing-image-retrieval
공식 코드Multi-Spectral Remote Sensing Image Retrieval Using Geospatial Foundation Models
https://github.com/ict-bigdatalab/vnel
공식 코드https://github.com/idstcv/SoftTriple
공식 코드SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
https://github.com/ifnspaml/s-amodal
공식 코드Foundation Models for Amodal Video Instance Segmentation in Automated Driving
https://github.com/imatge-upc/egocentric-2017-lta
공식 코드https://github.com/imatge-upc/retrieval-2017-cam
공식 코드Class-Weighted Convolutional Features for Visual Instance Search
https://github.com/imirandam/bivlc
공식 코드BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.