Papers with Code 아카이브

2D Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

27

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/6zhc/decun

공식 코드

Deep, convergent, unrolled half-quadratic splitting for image deconvolution

https://github.com/731935354/dia-sum-fact

공식 코드

Annotating and Detecting Fine-grained Factual Errors for Dialogue Summarization

https://github.com/7777777cc/code

공식 코드

BadRL: Sparse Targeted Backdoor Attack Against Reinforcement Learning

https://github.com/7eu7d7/robustdet

공식 코드

Adversarially-Aware Robust Object Detector

https://github.com/98chao/ProtoAD

공식 코드

A Prototype-Based Neural Network for Image Anomaly Detection and Localization

https://github.com/AAnoosheh/ToDayGAN

공식 코드

Night-to-Day Image Translation for Retrieval-based Localization

https://github.com/ADMSCentre/factchecking-presentations

공식 코드

Designing and Evaluating Presentation Strategies for Fact-Checked Content

https://github.com/AHupuJR/EFNet

공식 코드

Event-Based Fusion for Motion Deblurring with Cross-modal Attention

https://github.com/AIROTAU/TexLiDAR

공식 코드

TexLiDAR: Automated Text Understanding for Panoramic LiDAR Data

https://github.com/AIS-Bonn/stillleben

공식 코드

Stillleben: Realistic Scene Synthesis for Deep Learning in Robotics

https://github.com/AIS-Clemson/FLAME_SD

공식 코드

FLAME Diffuser: Wildfire Image Synthesis using Mask Guided Diffusion

https://github.com/AMiiR-S/Inceptnet_cancer_recognition

공식 코드

INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses

https://github.com/ART-Group-it/GASP

공식 코드

GASP! Generating Abstracts of Scientific Papers from Abstracts of Cited Papers

https://github.com/ASU-ESIC-FAN-Lab/DEEPDUPA

공식 코드

Deep-Dup: An Adversarial Weight Duplication Attack Framework to Crush Deep Neural Network in Multi-Tenant FPGA

https://github.com/Aadharc/Visual_Thermal_Image_Fusion

공식 코드

MISFIT-V: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual

https://github.com/Aaditya-Singh/SAFIN

공식 코드

SAFIN: Arbitrary Style Transfer With Self-Attentive Factorized Instance Normalization

https://github.com/AaronSun2000/MakeupAttack

공식 코드

MakeupAttack: Feature Space Black-box Backdoor Attack on Face Recognition via Makeup Transfer

https://github.com/AaronZ345/StyleSinger

공식 코드

StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis

https://github.com/AaronZ345/TCSinger

공식 코드

TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control

https://github.com/AbdelrhmanElnenaey/SIRR_MSloss_RefGAN_RDM

공식 코드

Utilizing Multi-step Loss for Single Image Reflection Removal

https://github.com/Abdullah-88/NiNformer

공식 코드

NiNformer: A Network in Network Transformer with Token Mixing Generated Gating Function

https://github.com/Abdullah-Abuolaim/defocus-deblurring-dual-pixel

공식 코드

Defocus Deblurring Using Dual-Pixel Data

https://github.com/Abdullah-Abuolaim/multi-task-defocus-deblurring-dual-pixel-nimat

공식 코드

Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning

https://github.com/Abdullah-Abuolaim/recurrent-defocus-deblurring-synth-dual-pixel

공식 코드

Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data

https://github.com/Abhishek0697/Detection-of-Hate-Speech-in-Multimodal-Memes

공식 코드

Detecting Hate Speech in Multi-modal Memes

https://github.com/AceSix/Knowledge_Transfer

공식 코드

Image Translation via Fine-grained Knowledge Transfer

https://github.com/ActiveVisionLab/porf

공식 코드

PoRF: Pose Residual Field for Accurate Neural Surface Reconstruction

https://github.com/Aiolus-X/RefConv

공식 코드

RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets

https://github.com/AkariAsai/XORQA

공식 코드

XOR QA: Cross-lingual Open-Retrieval Question Answering

https://github.com/AlaaLab/InstructCV

공식 코드

InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists

https://github.com/Alan-D-Chen/CDIoU-CDIoUloss

공식 코드

Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression

https://github.com/AlbertSuarez/object-cut

공식 코드

Boundary-Aware Segmentation Network for Mobile and Web Applications

https://github.com/Ale9806/eVLLM

공식 코드

μ-Bench: A Vision-Language Benchmark for Microscopy Understanding

https://github.com/AlejandroBarrera/birdnet2

공식 코드

BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View

https://github.com/Alex-Fabbri/Multi-News

공식 코드

Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model

https://github.com/AlexGidiotis/DANCER-summ

공식 코드

A Divide-and-Conquer Approach to the Summarization of Long Documents

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