https://github.com/zty0304/sgdraw
공식 코드SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation
Papers with Code 아카이브
Image Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 10
- 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://gitlab.com/srrg-software/srrg_bench
공식 코드Adding Cues to Binary Feature Descriptors for Visual Place Recognition
https://gitlab.com/srrg-software/srrg_hbst
공식 코드HBST: A Hamming Distance embedding Binary Search Tree for Visual Place Recognition
https://github.com/0jason000/wukong
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
https://github.com/2023-MindSpore-1/ms-code-107
SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval
https://github.com/2023-MindSpore-1/ms-code-161
OPT: Omni-Perception Pre-Trainer for Cross-Modal Understanding and Generation
https://github.com/2023-MindSpore-1/ms-code-18/tree/main/MCNN
Multimodal Convolutional Neural Networks for Matching Image and Sentence
https://github.com/2023-MindSpore-1/ms-code-62
MultiGrain: a unified image embedding for classes and instances
https://github.com/2023-MindSpore-1/ms-code-7
SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval
https://github.com/2023-MindSpore-4/Code3/tree/main/delf
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/blip_2
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/cogvlm
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/dinov2
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/falcon
https://github.com/2281123066/visual-semantic-embedding
Multimodal Convolutional Neural Networks for Matching Image and Sentence
https://github.com/394781865/insightface
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/AI4Patents/IMPACT
https://github.com/AU-DIS/ConQA
https://github.com/AUCOHL/RTL-Repo
https://github.com/AemikaChow/DATASOURCE
https://github.com/AggMan96/RK-Net
https://github.com/AlexMoreo/tensorflow-Text2Vis
Picture It In Your Mind: Generating High Level Visual Representations From Textual Descriptions
https://github.com/Aman-4-Real/MMTG
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
https://github.com/AmirSh15/FECNet
VGGFace2: A dataset for recognising faces across pose and age
https://github.com/AnasIbrahim/image_agnostic_segmentation
Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic Grasping
https://github.com/AndresPMD/Fine_Grained_Clf
https://github.com/AndresPMD/GCN_classification
Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval
https://github.com/AndresPMD/Pytorch-yolo-phoc
https://github.com/Andrew-Brown1/Smooth_AP
Smooth-AP: Smoothing the Path Towards Large-Scale Image Retrieval
https://github.com/Aniket7/Transfer-Learning
CNN Features off-the-shelf: an Astounding Baseline for Recognition
https://github.com/ArturPrzybysz/MNIST-siamese
https://github.com/Ash-Lee233/delf
Large-Scale Image Retrieval with Attentive Deep Local Features
https://github.com/AyanKumarBhunia/on-the-fly-FGSBIR
Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval
https://github.com/AyanKumarBhunia/semisupervised-FGSBIR
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval
https://github.com/BAAI-WuDao/BriVl
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
https://github.com/BR-IDL/PaddleViT/tree/develop/self_supervised_learning/dino
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.