Papers with Code 아카이브

2D Semantic Segmentation

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전체 기법전체 데이터셋

하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/mcg-nju/comae

공식 코드

CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D Datasets

https://github.com/mcg-nju/sportshhi

공식 코드

SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos

https://github.com/mcg-nju/structured-sparse-rcnn

공식 코드

Structured Sparse R-CNN for Direct Scene Graph Generation

https://github.com/mcg-nju/trace

공식 코드

Target Adaptive Context Aggregation for Video Scene Graph Generation

https://github.com/mcgrche/LetsPi--Planning-Safety-Trajectories-with-Dual-Phase-Physics-Informed-LLM

공식 코드

Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models

https://github.com/mcgregorwwww/uctransnet

공식 코드

UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer

https://github.com/mckellwoodland/dimen_reduce_mahal

공식 코드

Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation

https://github.com/mdyao/polarfree

공식 코드

PolarFree: Polarization-based Reflection-free Imaging

https://github.com/meclabtuda/atlas-replay

공식 코드

Continual atlas-based segmentation of prostate MRI

https://github.com/meclabtuda/med-nca

공식 코드

Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata

https://github.com/med-air/3dsam-adapter

공식 코드

3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

https://github.com/med-air/cmc

공식 코드

Robust Semi-supervised Multimodal Medical Image Segmentation via Cross Modality Collaboration

https://github.com/med-air/gazemedseg

공식 코드

Weakly-supervised Medical Image Segmentation with Gaze Annotations

https://github.com/med-air/iop-fl

공식 코드

IOP-FL: Inside-Outside Personalization for Federated Medical Image Segmentation

https://github.com/medaitech/rab

공식 코드

Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning

https://github.com/medaitech/tcmn

공식 코드

One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks

https://github.com/medicinetoken/medical-sam2

공식 코드

Medical SAM 2: Segment medical images as video via Segment Anything Model 2

https://github.com/medicl-vu/cats

공식 코드

CATS v2: Hybrid encoders for robust medical segmentation

https://github.com/medicl-vu/colossal

공식 코드

COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation

https://github.com/medicl-vu/promise

공식 코드

Promise:Prompt-driven 3D Medical Image Segmentation Using Pretrained Image Foundation Models

https://github.com/medicl-vu/variability

공식 코드

Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts

https://github.com/medimair/brain-mri-processing-pipeline

공식 코드

Negligible effect of brain MRI data preprocessing for tumor segmentation

https://github.com/mehmetaygun/4d-pls

공식 코드

4D Panoptic LiDAR Segmentation

https://github.com/meituan-automl/visionllama

공식 코드

VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks

https://github.com/melinphd/taal

공식 코드

TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation

https://github.com/melosy/cam

공식 코드

Class-Aware Mask-Guided Feature Refinement for Scene Text Recognition

https://github.com/menggerSherry/Trans_Fusion_Net

공식 코드

Exploiting full Resolution Feature Context for Liver Tumor and Vessel Segmentation via Integrate Framework: Application to Liver Tumor and Vessel 3D Reconstruction under embedded microprocessor

https://github.com/menglcool/segic

공식 코드

SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation

https://github.com/mengqi-lei/condseg

공식 코드

ConDSeg: A General Medical Image Segmentation Framework via Contrast-Driven Feature Enhancement

https://github.com/mengyunq/cheart

공식 코드

CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy

https://github.com/mengyuwang826/segrefiner

공식 코드

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

https://github.com/merantix/acosp

공식 코드

Auto-Compressing Subset Pruning for Semantic Image Segmentation

https://github.com/merantix/mxlabs-daain

공식 코드

DAAIN: Detection of Anomalous and Adversarial Input using Normalizing Flows

https://github.com/metamedseg/Code

공식 코드

MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ Segmentation

https://github.com/mfigurnov/sact

공식 코드

Spatially Adaptive Computation Time for Residual Networks

https://github.com/mguti97/soccernet-v3d

공식 코드

SoccerNet-v3D: Leveraging Sports Broadcast Replays for 3D Scene Understanding

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