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보존된 평가 기록

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코드

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

https://github.com/JianboGuo/network-decoupling

공식 코드

Network Decoupling: From Regular to Depthwise Separable Convolutions

https://github.com/Jianf-Wang/GRCNN

공식 코드

Convolutional Neural Networks with Gated Recurrent Connections

https://github.com/JiaxiHe/Image-and-Video-Dehazing

공식 코드

Fast Single Image Dehazing via Multilevel Wavelet Transform based Optimization

https://github.com/JinYuanLi0012/RiVEG

공식 코드

LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition

https://github.com/JingZhang617/COD-Rank-Localize-and-Segment

공식 코드

Simultaneously Localize, Segment and Rank the Camouflaged Objects

https://github.com/JingZhang617/Joint_COD_SOD

공식 코드

Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

https://github.com/JingZhang617/Scribble_Saliency

공식 코드

Weakly-Supervised Salient Object Detection via Scribble Annotations

https://github.com/JingZhang617/UCNet

공식 코드

Uncertainty Inspired RGB-D Saliency Detection

https://github.com/JingbiaoMei/BayesFTNA

공식 코드

BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture

https://github.com/JingyunLiang/FKP

공식 코드

Flow-based Kernel Prior with Application to Blind Super-Resolution

https://github.com/Jinming-Su/PurNet

공식 코드

Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss

https://github.com/Jinming-Su/TSOD

공식 코드

Exploring Driving-aware Salient Object Detection via Knowledge Transfer

https://github.com/Jittor/JDet

공식 코드

The KFIoU Loss for Rotated Object Detection

https://github.com/JoeRoussy/adaptive-attention-in-cv

공식 코드

Adaptive Attention Span in Computer Vision

https://github.com/Johann-Huber/qd_grasp

공식 코드

Toward a Plug-and-Play Vision-Based Grasping Module for Robotics

https://github.com/Johnathan-Xie/ZSD-YOLO

공식 코드

Zero-shot Object Detection Through Vision-Language Embedding Alignment

https://github.com/JosephChenHub/DPANet

공식 코드

DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection

https://github.com/JosephChenHub/GCPANet

공식 코드

Global Context-Aware Progressive Aggregation Network for Salient Object Detection

https://github.com/JosephKJ/OWOD

공식 코드

Towards Open World Object Detection

https://github.com/JosephKJ/iOD

공식 코드

Incremental Object Detection via Meta-Learning

https://github.com/JudasDie/SOTS

공식 코드

One More Check: Making "Fake Background" Be Tracked Again

https://github.com/Jun-Pu/UCOS-DA

공식 코드

Unsupervised Camouflaged Object Segmentation as Domain Adaptation

https://github.com/KIT-MRT/YOLinO

공식 코드

YOLinO: Generic Single Shot Polyline Detection in Real Time

https://github.com/KPeng9510/MASS

공식 코드

MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understanding

https://github.com/KaimingHe/resnet-1k-layers

공식 코드

Deep Residual Learning for Image Recognition

https://github.com/KaiyuYue/cgnl-network.pytorch

공식 코드

Compact Generalized Non-local Network

https://github.com/KangchengLiu/FAC_Foreground_Aware_Contrast

공식 코드

Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast

https://github.com/KangchengLiu/RM3D

공식 코드

A Data-efficient Framework for Robotics Large-scale LiDAR Scene Parsing

https://github.com/Karel911/TRACER

공식 코드

TRACER: Extreme Attention Guided Salient Object Tracing Network

https://github.com/KenYu910645/perspective-aware-convolution

공식 코드

Perspective-aware Convolution for Monocular 3D Object Detection

https://github.com/KimSoybean/ScratchDet

공식 코드

ScratchDet: Training Single-Shot Object Detectors from Scratch

https://github.com/KiveeDong/CentripetalNet

공식 코드

CentripetalNet: Pursuing High-quality Keypoint Pairs for Object Detection

https://github.com/KostadinovShalon/UAVDetectionTrackingBenchmark

공식 코드

Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark

https://github.com/KostadinovShalon/fever-ood

공식 코드

FEVER-OOD: Free Energy Vulnerability Elimination for Robust Out-of-Distribution Detection

https://github.com/Kthyeon/ssfod

공식 코드

Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Federated Object Detection

https://github.com/KupynOrest/DeblurGAN

공식 코드

DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks

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