Papers with Code 아카이브

Semantic Segmentation

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하위 태스크

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코드

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

https://github.com/osvai/ssd-kd

공식 코드

Small Scale Data-Free Knowledge Distillation

https://github.com/othmanela/certified_segmentation

공식 코드

Towards Better Certified Segmentation via Diffusion Models

https://github.com/othmanela/medical_cert_seg

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Certification of Deep Learning Models for Medical Image Segmentation

https://github.com/oucailab/afenet

공식 코드

Adaptive Frequency Enhancement Network for Remote Sensing Image Semantic Segmentation

https://github.com/ouenal/scribblekitti

공식 코드

Scribble-Supervised LiDAR Semantic Segmentation

https://github.com/oulu-imeds/log-vmamba

공식 코드

LoG-VMamba: Local-Global Vision Mamba for Medical Image Segmentation

https://github.com/oulu-imeds/sauna

공식 코드

Image-level Regression for Uncertainty-aware Retinal Image Segmentation

https://github.com/oulu-imeds/singr

공식 코드

SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression

https://github.com/ouyangjiahong/representation-disentanglement

공식 코드

Representation Disentanglement for Multi-modal brain MR Analysis

https://github.com/overlapping-instances/MultiStar

공식 코드

MultiStar: Instance Segmentation of Overlapping Objects with Star-Convex Polygons

https://github.com/ovo1111/efficientsubclasslearning

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Efficient Subclass Segmentation in Medical Images

https://github.com/ovo1111/jointimagegeneration

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GuideGen: A Text-Guided Framework for Full-torso Anatomy and CT Volume Generation

https://github.com/owenzlz/egohos

공식 코드

Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications

https://github.com/ozan-oktay/Attention-Gated-Networks

공식 코드

Attention U-Net: Learning Where to Look for the Pancreas

https://github.com/ozzyou/autoseg

공식 코드

Auto-Vocabulary Semantic Segmentation

https://github.com/ozzyou/rp-fem

공식 코드

Relational Prior Knowledge Graphs for Detection and Instance Segmentation

https://github.com/p-shekhar/adversarial-patch-transferability

공식 코드

Cross-Model Transferability of Adversarial Patches in Real-time Segmentation for Autonomous Driving

https://github.com/pab1s/granada-parking-segmentation

공식 코드

Parking Space Detection in the City of Granada

https://github.com/pablohc97/TFM

공식 코드

Neural Networks with Divisive normalization for image segmentation with application in cityscapes dataset

https://github.com/pagand/e2etransfuser

공식 코드

LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for Autonomous Driving with Multi-Task Learning

https://github.com/pagraf/MagicBathyNet

공식 코드

MagicBathyNet: A Multimodal Remote Sensing Dataset for Bathymetry Prediction and Pixel-based Classification in Shallow Waters

https://github.com/palmdong/smmcl

공식 코드

Understanding Dark Scenes by Contrasting Multi-Modal Observations

https://github.com/pancakewaffles/metasrgan-tutorial

공식 코드

Arbitrary Scale Super-Resolution for Brain MRI Images

https://github.com/pansanity666/INO_VOS

공식 코드

In-N-Out Generative Learning for Dense Unsupervised Video Segmentation

https://github.com/panzhiyi/aadnet

공식 코드

Point Cloud Semantic Segmentation with Sparse and Inhomogeneous Annotations

https://github.com/paolomandica/HALO

공식 코드

Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

https://github.com/pardistaghavi/swinmtl

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SwinMTL: A Shared Architecture for Simultaneous Depth Estimation and Semantic Segmentation from Monocular Camera Images

https://github.com/parshwa1999/PeR-ViS

공식 코드

PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description

https://github.com/pascalcpp/sdcl

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SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation

https://github.com/pashtari/deconver

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Deconver: A Deconvolutional Network for Medical Image Segmentation

https://github.com/pashtari/factorizer

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Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation

https://github.com/pasqualedem/LabelAnything

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Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts

https://github.com/pathak22/ccnn

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Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

https://github.com/pathak22/seg-by-interaction

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Learning Instance Segmentation by Interaction

https://github.com/patrick-knab/dseg-lime

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Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation Models

https://github.com/patrick-tssn/VSTAR

공식 코드

VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions

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