Papers with Code 아카이브

2D Semantic Segmentation

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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/tlliao/multi-homo-warp

공식 코드

Parallax-tolerant Image Stitching via Segmentation-guided Multi-homography Warping

https://github.com/tntek/dspnet

공식 코드

Few-Shot Medical Image Segmentation with High-Fidelity Prototypes

https://github.com/tobiaskalb/disjoint_cityscape_splits

공식 코드

Improving Replay-Based Continual Semantic Segmentation with Smart Data Selection

https://github.com/tobran/galip

공식 코드

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

https://github.com/toggle1995/ris-dmmi

공식 코드

Beyond One-to-One: Rethinking the Referring Image Segmentation

https://github.com/tomer196/PILOT

공식 코드

PILOT: Physics-Informed Learned Optimized Trajectories for Accelerated MRI

https://github.com/tomeramit/SegDiff

공식 코드

SegDiff: Image Segmentation with Diffusion Probabilistic Models

https://github.com/tomeramit/annotator-consensus-prediction

공식 코드

Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models

https://github.com/tomtang502/graphseg

공식 코드

GraphSeg: Segmented 3D Representations via Graph Edge Addition and Contraction

https://github.com/toneyaya/cgformer

공식 코드

Contrastive Grouping with Transformer for Referring Image Segmentation

https://github.com/tong-zeng/dvbench

공식 코드

Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understanding

https://github.com/tongkunguan/ccd

공식 코드

Self-supervised Character-to-Character Distillation for Text Recognition

https://github.com/tongkunguan/siga

공식 코드

Self-supervised Implicit Glyph Attention for Text Recognition

https://github.com/tooploox/plugin-networks

공식 코드

Plugin Networks for Inference under Partial Evidence

https://github.com/topdu/openocr

공식 코드

Instruction-Guided Scene Text Recognition

https://github.com/topoxlab/topointeraction

공식 코드

Learning Topological Interactions for Multi-Class Medical Image Segmentation

https://github.com/toqitahamid/gasformer

공식 코드

Gasformer: A Transformer-based Architecture for Segmenting Methane Emissions from Livestock in Optical Gas Imaging

https://github.com/torpedo2648/pclmix

공식 코드

PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix Augmentation

https://github.com/torrvision/crfasrnn

공식 코드

Conditional Random Fields as Recurrent Neural Networks

https://github.com/toyotainfotech/stisr-tcdm

공식 코드

Scene Text Image Super-resolution based on Text-conditional Diffusion Models

https://github.com/tpnam0901/QTSeg

공식 코드

QTSeg: A Query Token-Based Architecture for Efficient 2D Medical Image Segmentation

https://github.com/tpopordanoska/calibration_and_bias

공식 코드

On the relationship between calibrated predictors and unbiased volume estimation

https://github.com/tqwei05/PlantSeg

공식 코드

PlantSeg: A Large-Scale In-the-wild Dataset for Plant Disease Segmentation

https://github.com/tranleanh/edn-gtm

공식 코드

A Novel Encoder-Decoder Network with Guided Transmission Map for Single Image Dehazing

https://github.com/tranngocduvnvp/litenext

공식 코드

LiteNeXt: A Novel Lightweight ConvMixer-based Model with Self-embedding Representation Parallel for Medical Image Segmentation

https://github.com/tri-ml/prismatic-vlms

공식 코드

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

https://github.com/tri-ml/vedet

공식 코드

Viewpoint Equivariance for Multi-View 3D Object Detection

https://github.com/tri-ml/vlm-evaluation

공식 코드

Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models

https://github.com/trile83/rqunetvae

공식 코드

Riesz-Quincunx-UNet Variational Auto-Encoder for Satellite Image Denoising

https://github.com/triumph123aaa/grid-augmented-vision

공식 코드

Grid-augmented vision: A simple yet effective approach for enhanced spatial understanding in multi-modal agents

https://github.com/trustworthy-ai-uu-nki/cross-modal-segmentation

공식 코드

Enhancing Cross-Modal Medical Image Segmentation through Compositionality

https://github.com/trustworthy-ai-uu-nki/federated-learning-disentanglement

공식 코드

FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentation

https://github.com/tsinghua-mars-lab/trackocc

공식 코드

TrackOcc: Camera-based 4D Panoptic Occupancy Tracking

https://github.com/tsumansapkota/Input-Invex-Neural-Network

공식 코드

Input Invex Neural Network

https://github.com/tsunghan-wu/redal

공식 코드

ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation

https://github.com/tue-mps/eomt

공식 코드

Your ViT is Secretly an Image Segmentation Model

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