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2D Classification

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전체 기법전체 데이터셋

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코드

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

https://github.com/sciencefans/RSA-for-object-detection

공식 코드

Recurrent Scale Approximation for Object Detection in CNN

https://github.com/scjjb/midog_domain_adaptation

공식 코드

Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images

https://github.com/sclbd/backdoorbench

공식 코드

BackdoorBench: A Comprehensive Benchmark of Backdoor Learning

https://github.com/scnu-rislab/yolo-ant

공식 코드

YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detection

https://github.com/scoopmatic/finnish-hockey-news-generation-paper

공식 코드

Template-free Data-to-Text Generation of Finnish Sports News

https://github.com/scuwyh2000/randbox

공식 코드

Random Boxes Are Open-world Object Detectors

https://github.com/sczhou/LEDNet

공식 코드

LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

https://github.com/sdbuch/refine

공식 코드

Resource-Efficient Invariant Networks: Exponential Gains by Unrolled Optimization

https://github.com/sdoerrich97/vits-are-generative-models

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Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization

https://github.com/sdy1999/eamnet

공식 코드

Edge-Aware Mirror Network for Camouflaged Object Detection

https://github.com/seanxuu/PWISeg

공식 코드

PWISeg: Point-based Weakly-supervised Instance Segmentation for Surgical Instruments

https://github.com/seanzhuh/awesome-open-vocabulary-detection-and-segmentation

공식 코드

A Survey on Open-Vocabulary Detection and Segmentation: Past, Present, and Future

https://github.com/seaocn/link-backdoor

공식 코드

Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection

https://github.com/seaocn/motif-backdoor

공식 코드

Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via Motifs

https://github.com/sebajoe/multicochrane

공식 코드

Multilingual Simplification of Medical Texts

https://github.com/sebgao/LIP

공식 코드

LIP: Local Importance-based Pooling

https://github.com/sebischair/fusionsent

공식 코드

Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes

https://github.com/sebischair/kg-conv-exploratory-search

공식 코드

From Data to Dialogue: Leveraging the Structure of Knowledge Graphs for Conversational Exploratory Search

https://github.com/secure-ai-systems-group/qu-anti-zation

공식 코드

Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes

https://github.com/seermer/RTGen

공식 코드

RTGen: Generating Region-Text Pairs for Open-Vocabulary Object Detection

https://github.com/sefaburakokcu/finn-quantized-yolo

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LPYOLO: Low Precision YOLO for Face Detection on FPGA

https://github.com/sefeoglu/coronanews-ner

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Fine-Grained Named Entities for Corona News

https://github.com/segments-ai/latent-diffusion-segmentation

공식 코드

A Simple Latent Diffusion Approach for Panoptic Segmentation and Mask Inpainting

https://github.com/sekilab/RoadDamageDetector

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Road Damage Detection Using Deep Neural Networks with Images Captured Through a Smartphone

https://github.com/sekunde/pri3d

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Pri3D: Can 3D Priors Help 2D Representation Learning?

https://github.com/selinakhan/CIGAr

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Context-Infused Visual Grounding for Art

https://github.com/selvamsriram/panorama-datagen

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PANORAMA: A synthetic PII-laced dataset for studying sensitive data memorization in LLMs

https://github.com/semanto-mondal/A-RAG-Augmented-YOLOv8-Framework

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Vision Meets Language: A RAG-Augmented YOLOv8 Framework for Coffee Disease Diagnosis and Farmer Assistance

https://github.com/semchan/NLUT

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NLUT: Neural-based 3D Lookup Tables for Video Photorealistic Style Transfer

https://github.com/semchan/UPST-NeRF

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UPST-NeRF: Universal Photorealistic Style Transfer of Neural Radiance Fields for 3D Scene

https://github.com/sense-x/agvm

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Large-batch Optimization for Dense Visual Predictions

https://github.com/sense-x/geomim

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GeoMIM: Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding

https://github.com/sense-x/hop

공식 코드

Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction

https://github.com/sense-x/mixmim

공식 코드

MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers

https://github.com/sense-x/unihead

공식 코드

Unifying Visual Perception by Dispersible Points Learning

https://github.com/senwang98/monoskd

공식 코드

MonoSKD: General Distillation Framework for Monocular 3D Object Detection via Spearman Correlation Coefficient

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