https://github.com/vevenom/pytorchgeonodes
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape Reconstruction
Papers with Code 아카이브
Retrieval
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 11
- 보존된 평가 기록
- 19
A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/viditjain99/TripletGAN
https://github.com/vijaynchakole/HUSE-Hierarchical-Universal-Semantic-Embeddings
https://github.com/vinnik-dmitry07/PlaceRecognition
NetVLAD: CNN architecture for weakly supervised place recognition
https://github.com/vita-group/abd-net
https://github.com/vividwalker/Multi-Head-Rag
https://github.com/vl2g/CSTBIR
Composite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex Interactions
https://github.com/vladsandulescu/hatefulmemes
https://github.com/vlsomers/keypoint_promptable_reidentification
Body Part-Based Representation Learning for Occluded Person Re-Identification
https://github.com/vmurahari3/visdial-bert
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/vohoaiviet/retrieval-2016-deepvision
https://github.com/voidism/dola
Generating Benchmarks for Factuality Evaluation of Language Models
https://github.com/vpariza/open-hummingbird-eval
https://github.com/vukbatanovic/SCStemmers
https://github.com/vyraun/Half-Size
Simple and Effective Dimensionality Reduction for Word Embeddings
https://github.com/wadoodabdul/clinical_ner_benchmark
https://github.com/wasiahmad/context_attentive_ir
https://github.com/wasiahmad/mnsrf_ranking_suggestion
https://github.com/weirdlabuw/strap
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
https://github.com/weitong8591/ars_magsac
https://github.com/weixuan-wang123/ReMaKE
https://github.com/weiyinwei/GCN_PHR
Separating Self-Expression and Visual Content in Hashtag Supervision
https://github.com/whut-yirong/espt
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning
https://github.com/whwu95/BIKE
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/whwu95/GPT4Vis
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/whwu95/text4vis
Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?
https://github.com/wickstrom/relax
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
https://github.com/willard-yuan/video-text-retrieval-papers
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
https://github.com/willemsenbram/mention-detection-vgd
https://github.com/winstonll/SynC
Music Artist Classification with Convolutional Recurrent Neural Networks
https://github.com/winstonll/Synthetic_Population
Music Artist Classification with Convolutional Recurrent Neural Networks
https://github.com/wujpbb7/caffe_circleloss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/wvangansbeke/Unsupervised-Classification
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
https://github.com/wxb589/Person_reID_baseline_pytorch-master
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
https://github.com/x-plug/mplug
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
https://github.com/xch-liu/geom-tex-dg
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.