Papers with Code 아카이브

16k

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

6

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/znaoya/aenet

공식 코드

AENet: Learning Deep Audio Features for Video Analysis

https://github.com/zongdai/autoshape

공식 코드

AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

https://github.com/zongwei97/popnet

공식 코드

Source-free Depth for Object Pop-out

https://github.com/zongzi13545329/simada

공식 코드

SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes

https://github.com/zononhzy/lamnet

공식 코드

Unifying Dimensions: A Linear Adaptive Approach to Lightweight Image Super-Resolution

https://github.com/zoomin-lee/semcity

공식 코드

SemCity: Semantic Scene Generation with Triplane Diffusion

https://github.com/zpc456/akmd-net

공식 코드

Jointly RS Image Deblurring and Super-Resolution with Adjustable-Kernel and Multi-Domain Attention

https://github.com/zpdu/dai-net

공식 코드

Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation

https://github.com/zpywhu/pointobb-v3

공식 코드

PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection

https://github.com/zq-zang/descreg

공식 코드

Zero-Shot Aerial Object Detection with Visual Description Regularization

https://github.com/zqyq/Mahalanobis-Distance-based-Multi-view-Optimal-Transport-for-Multi-view-Crowd-Localization

공식 코드

Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization

https://github.com/zqyq/Multi-view-People-Detection-in-Large-Scenes-via-View-wise-Contribution-Weighting

공식 코드

Multi-View People Detection in Large Scenes via Supervised View-Wise Contribution Weighting

https://github.com/zrrskywalker/monodetr

공식 코드

MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection

https://github.com/zrrskywalker/point-m2ae

공식 코드

Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

https://github.com/zrrskywalker/pointclip

공식 코드

PointCLIP: Point Cloud Understanding by CLIP

https://github.com/zsc15/HPPP

공식 코드

HPPP: Halpern-type Preconditioned Proximal Point Algorithms and Applications to Image Restoration

https://github.com/zshanggu/cdmm

공식 코드

Cross-domain Multi-modal Few-shot Object Detection via Rich Text

https://github.com/zshanggu/htrpn

공식 코드

Identification of Novel Classes for Improving Few-Shot Object Detection

https://github.com/zsniko/ednet

공식 코드

EDNet: Edge-Optimized Small Target Detection in UAV Imagery -- Faster Context Attention, Better Feature Fusion, and Hardware Acceleration

https://github.com/zsyOAOA/BSRDM

공식 코드

Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel

https://github.com/zsyOAOA/VIRNet

공식 코드

Deep Variational Network Toward Blind Image Restoration

https://github.com/zsyasd/excavating-roi-attention-for-underwater-object-detection

공식 코드

Excavating RoI Attention for Underwater Object Detection

https://github.com/zsyoaoa/invsr

공식 코드

Arbitrary-steps Image Super-resolution via Diffusion Inversion

https://github.com/zsyoaoa/resshift

공식 코드

ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting

https://github.com/zth667/Diverse-Image-Synthesis-from-Semantic-Layout

공식 코드

Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation

https://github.com/ztt1024/densessl

공식 코드

De-coupling and De-positioning Dense Self-supervised Learning

https://github.com/ztx-100/dla-combined-ious

공식 코드

Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs

https://github.com/ztx-100/efficient_vit_with_dw

공식 코드

Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets

https://github.com/zubair-irshad/NeRF-MAE

공식 코드

NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields

https://github.com/zubair-irshad/shapo

공식 코드

ShAPO: Implicit Representations for Multi-Object Shape, Appearance, and Pose Optimization

https://github.com/zudi-lin/rcan-it

공식 코드

Revisiting RCAN: Improved Training for Image Super-Resolution

https://github.com/zwbx/BTS-Net

공식 코드

BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection

https://github.com/zwbx/DFM-Net

공식 코드

Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection

https://github.com/zxcvfd13502/ddas_code

공식 코드

Direct Differentiable Augmentation Search

https://github.com/zxlation/FC2N

공식 코드

FC$^2$N: Fully Channel-Concatenated Network for Single Image Super-Resolution

https://github.com/zyfone/dpa

공식 코드

Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment

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