Papers with Code 아카이브

Semantic Segmentation

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코드

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

https://github.com/google/quickshift

공식 코드

Quickshift++: Provably Good Initializations for Sample-Based Mean Shift

https://github.com/google/uncertainty-baselines

공식 코드

On the Practicality of Deterministic Epistemic Uncertainty

https://github.com/google/xr-objects

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Augmented Object Intelligence with XR-Objects

https://github.com/googleinterns/wss

공식 코드

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation

https://github.com/gorilla-lab-scut/sstnet

공식 코드

Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

https://github.com/gqding/SUDF

공식 코드

Salient object detection on hyperspectral images using features learned from unsupervised segmentation task

https://github.com/gramuah/semnav

공식 코드

SEMNAV: A Semantic Segmentation-Driven Approach to Visual Semantic Navigation

https://github.com/gramuah/weakly-supervised-segmentation

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Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation

https://github.com/grandzxw/triplemixer

공식 코드

TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weather

https://github.com/grantword8/blv

공식 코드

Balancing Logit Variation for Long-tailed Semantic Segmentation

https://github.com/greekinroma/kmndnet

공식 코드

SMPISD-MTPNet: Scene Semantic Prior-Assisted Infrared Ship Detection Using Multi-Task Perception Networks

https://github.com/griffbr/BubbleNets

공식 코드

BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames

https://github.com/griffbr/ODMS

공식 코드

Learning Object Depth from Camera Motion and Video Object Segmentation

https://github.com/griffbr/TIS

공식 코드

Tukey-Inspired Video Object Segmentation

https://github.com/griffbr/supervoxel-gerrymandering

공식 코드

Video Object Segmentation using Supervoxel-Based Gerrymandering

https://github.com/gritzner/segforestnet

공식 코드

SegForestNet: Spatial-Partitioning-Based Aerial Image Segmentation

https://github.com/grokcv/bafe-net

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Background Semantics Matter: Cross-Task Feature Exchange Network for Clustered Infrared Small Target Detection With Sky-Annotated Dataset

https://github.com/gtlinyer/LOANet

공식 코드

LOANet: A Lightweight Network Using Object Attention for Extracting Buildings and Roads from UAV Aerial Remote Sensing Images

https://github.com/guanfangdong/lts-univerisalmos

공식 코드

Learning Temporal Distribution and Spatial Correlation Towards Universal Moving Object Segmentation

https://github.com/guanghaozhu663/astmatch

공식 코드

AstMatch: Adversarial Self-training Consistency Framework for Semi-Supervised Medical Image Segmentation

https://github.com/guanlinlee/noisy-lvis

공식 코드

A Benchmark of Long-tailed Instance Segmentation with Noisy Labels

https://github.com/guanrunwei/asy-vrnet

공식 코드

ASY-VRNet: Waterway Panoptic Driving Perception Model based on Asymmetric Fair Fusion of Vision and 4D mmWave Radar

https://github.com/guanxiongsun/stpn

공식 코드

Spatio-temporal Prompting Network for Robust Video Feature Extraction

https://github.com/guanxiongsun/vfe.pytorch

공식 코드

Spatio-temporal Prompting Network for Robust Video Feature Extraction

https://github.com/gudovskiy/flowenedet

공식 코드

Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow

https://github.com/gugarosa/opfython

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OPFython: A Python-Inspired Optimum-Path Forest Classifier

https://github.com/gugu511yy/ptq4ris

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PTQ4RIS: Post-Training Quantization for Referring Image Segmentation

https://github.com/gugull123/stac

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Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation

https://github.com/guigzos/crossmodalgba

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Cross-modal tumor segmentation using generative blending augmentation and self training

https://github.com/guilherme-pombo/3DPixelCNN

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Bayesian Volumetric Autoregressive generative models for better semisupervised learning

https://github.com/guillermo-jimenez/ECGDelNet

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ECG-DelNet: Delineation of Ambulatory Electrocardiograms with Mixed Quality Labeling Using Neural Networks

https://github.com/guochengqian/assanet

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ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning

https://github.com/guochengqian/openpoints/blob/master/models/backbone/pointvector.py

공식 코드

PointVector: A Vector Representation In Point Cloud Analysis

https://github.com/guochengqian/pix4point

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Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding

https://github.com/guochengqian/pointnext

공식 코드

PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

https://github.com/guoleisun/vss-cffm

공식 코드

Learning Local and Global Temporal Contexts for Video Semantic Segmentation

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