Papers with Code 아카이브

Sketch Recognition

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/PengBoXiangShang/multigraph_transformer

공식 코드

Multi-Graph Transformer for Free-Hand Sketch Recognition

https://github.com/cai-jianfeng/flowmind2digital

공식 코드

Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion Approach

https://github.com/cogtoolslab/visual_abstractions_benchmarking_public2023

공식 코드

SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction

https://github.com/dnap512/SelfReg

공식 코드

SelfReg: Self-supervised Contrastive Regularization for Domain Generalization

https://github.com/erilyth/DistributionAwareBinarizedNetworks-WACV18

공식 코드

Distribution-Aware Binarization of Neural Networks for Sketch Recognition

https://github.com/explainableml/sketch-primitives

공식 코드

Abstracting Sketches through Simple Primitives

https://github.com/guangmingzhu/sketchesc

공식 코드

Enhance Sketch Recognition's Explainability via Semantic Component-Level Parsing

https://github.com/leekyungmoon/XDED

공식 코드

Cross-Domain Ensemble Distillation for Domain Generalization

https://github.com/liangchen527/itta

공식 코드

Improved Test-Time Adaptation for Domain Generalization

https://github.com/nikosefth/crafting-shifts

공식 코드

Crafting Distribution Shifts for Validation and Training in Single Source Domain Generalization

https://github.com/nikosefth/im2rbte

공식 코드

Edge Augmentation for Large-Scale Sketch Recognition without Sketches

https://github.com/val-iisc/sketch-obj-rec

공식 코드

Enabling My Robot To Play Pictionary : Recurrent Neural Networks For Sketch Recognition

https://github.com/avalonstrel/SketchBERT

Sketch-BERT: Learning Sketch Bidirectional Encoder Representation from Transformers by Self-supervised Learning of Sketch Gestalt

https://github.com/cmach508/sp-gra2seq

Sketch-a-Net that Beats Humans

https://github.com/dasayan05/sketchanet-quickdraw

Sketch-a-Net that Beats Humans

https://github.com/facebookresearch/DomainBed

Reducing Domain Gap by Reducing Style Bias

https://github.com/hyeonseobnam/sagnet

Reducing Domain Gap by Reducing Style Bias

https://github.com/hyeonseobnam/style-agnostic-networks

Reducing Domain Gap by Reducing Style Bias

https://github.com/sczang/dc-gra2seq

Sketch-a-Net that Beats Humans

https://github.com/tosmaster/imagevision

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.