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Semantic Segmentation

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하위 태스크

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150

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코드

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

https://github.com/edi-meta-learning/meta-omnium

공식 코드

Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn

https://github.com/edm-research/cut-and-splat

공식 코드

Cut-and-Splat: Leveraging Gaussian Splatting for Synthetic Data Generation

https://github.com/edornd/contrastive-distillation

공식 코드

A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images

https://github.com/edwardyehuang/CAA

공식 코드

Channelized Axial Attention for Semantic Segmentation -- Considering Channel Relation within Spatial Attention for Semantic Segmentation

https://github.com/edwardyehuang/CAR

공식 코드

CAR: Class-aware Regularizations for Semantic Segmentation

https://github.com/edwardzhou130/Panoptic-PolarNet

공식 코드

Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentation

https://github.com/edwardzhou130/PolarSeg

공식 코드

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

https://github.com/eerdil/task_agnostic_ood

공식 코드

Task-agnostic Out-of-Distribution Detection Using Kernel Density Estimation

https://github.com/eerik98/lidar-camera-road-autolabeling

공식 코드

Trajectory-based Road Autolabeling with Lidar-Camera Fusion in Winter Conditions

https://github.com/egeozsoy/MM-OR

공식 코드

MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments

https://github.com/egstatsml/eu-seg

공식 코드

Uncertainty in Real-Time Semantic Segmentation on Embedded Systems

https://github.com/eheinert/reducing-texture-bias-of-dnns-via-eed

공식 코드

Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion

https://github.com/eheinert/uncertainty-and-prediction-quality-estimation-for-semseg-via-gnns

공식 코드

Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks

https://github.com/ehoogeboom/multinomial_diffusion

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Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

https://github.com/elchiou/beyond-deterministic-translation-for-uda

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Beyond Deterministic Translation for Unsupervised Domain Adaptation

https://github.com/elharroussomar/awesome-panoptic-segmentation

공식 코드

Panoptic Segmentation: A Review

https://github.com/eli-yili/pmm

공식 코드

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation

https://github.com/elitap/classimbalance

공식 코드

Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation

https://github.com/elliesch/flipnslide

공식 코드

A Concise Tiling Strategy for Preserving Spatial Context in Earth Observation Imagery

https://github.com/elliotvincent/sitsscd

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Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shift

https://github.com/elnino9ykl/DS-PASS

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DS-PASS: Detail-Sensitive Panoramic Annular Semantic Segmentation through SwaftNet for Surrounding Sensing

https://github.com/elnino9ykl/WildPASS

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Capturing Omni-Range Context for Omnidirectional Segmentation

https://github.com/emanuelevivoli/awesome-comics-understanding

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One missing piece in Vision and Language: A Survey on Comics Understanding

https://github.com/emb-ai/rclicks

공식 코드

RClicks: Realistic Click Simulation for Benchmarking Interactive Segmentation

https://github.com/embar111/pgpc

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Pseudolabel guided pixels contrast for domain adaptive semantic segmentation

https://github.com/emi-group/evoxbench

공식 코드

A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic Segmentation

https://github.com/emiyajojo/Modular-Grasp-CNN

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Modular Anti-noise Deep Learning Network for Robotic Grasp Detection Based on RGB Images

https://github.com/endoluminalsurgicalvision-imr/acnorm

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AC-Norm: Effective Tuning for Medical Image Analysis via Affine Collaborative Normalization

https://github.com/endoluminalsurgicalvision-imr/ccfv

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Pick the Best Pre-trained Model: Towards Transferability Estimation for Medical Image Segmentation

https://github.com/endoluminalsurgicalvision-imr/ismm

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ReshapeIT: Reliable Shape Interaction with Implicit Template for Anatomical Structure Reconstruction

https://github.com/endoluminalsurgicalvision-imr/pass

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PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation

https://github.com/engelnico/point-transformer

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Point Transformer

https://github.com/engineerJPark/LiDAR-DataAug4Weather

공식 코드

Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather

https://github.com/engineerJPark/ORANDNet

공식 코드

Precision matters: Precision-aware ensemble for weakly supervised semantic segmentation

https://github.com/engineerjpark/lidarweather

공식 코드

Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather

https://github.com/engrjavediqbal/MLSL

공식 코드

MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling

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