https://github.com/risabbiswas/knowledge-distillation-in-medical-image-segmentation
공식 코드Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image Segmentation
Papers with Code 아카이브
2D Semantic Segmentation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/risabbiswas/polyp-sam
공식 코드Polyp-SAM++: Can A Text Guided SAM Perform Better for Polyp Segmentation?
https://github.com/rkwitt/GuidedAugmentation
공식 코드https://github.com/rkzheng99/villa
공식 코드ViLLa: Video Reasoning Segmentation with Large Language Model
https://github.com/rll-research/sim2seg
공식 코드Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data
https://github.com/rlqja1107/NL-VSGG
공식 코드Weakly Supervised Video Scene Graph Generation via Natural Language Supervision
https://github.com/rlqja1107/torch-LLM4SGG
공식 코드LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation
https://github.com/rlqja1107/torch-st-sgg
공식 코드Adaptive Self-training Framework for Fine-grained Scene Graph Generation
https://github.com/roadonep/eccv2024_mbs
공식 코드Mitigating Background Shift in Class-Incremental Semantic Segmentation
https://github.com/roatienza/deep-text-recognition-benchmark
공식 코드Vision Transformer for Fast and Efficient Scene Text Recognition
https://github.com/roatienza/straug
공식 코드https://github.com/robbergen/trgan
공식 코드Assessing Privacy Leakage in Synthetic 3-D PET Imaging using Transversal GAN
https://github.com/robert80203/GSVNet
공식 코드GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video
https://github.com/robertluo1/iccv2023_rvos_challenge
공식 코드1st Place Solution for 5th LSVOS Challenge: Referring Video Object Segmentation
https://github.com/robertwyq/panoocc
공식 코드PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation
https://github.com/robotic-vision-lab/few-shot-fruit-segmentation-via-transfer-learning
공식 코드https://github.com/robotics-upo/og-sgg
공식 코드https://github.com/robotvisionmu/densemonoslam
공식 코드A Hybrid Sparse-Dense Monocular SLAM System for Autonomous Driving
https://github.com/robustml-eurecom/Vessel-Captcha
공식 코드Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation
https://github.com/robustml-eurecom/quality_control_CMR
공식 코드Efficient Model Monitoring for Quality Control in Cardiac Image Segmentation
https://github.com/robustsam/RobustSAM
공식 코드https://github.com/rohit-kundu/ideal-icassp23
공식 코드IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentation
https://github.com/rohithpeddi/scenesayer
공식 코드https://github.com/rolsheng/mm-vufm4ds
공식 코드https://github.com/rongfu-dsb/MPG-SAM2
공식 코드https://github.com/rongzhao-zhang/ag-crc
공식 코드AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical Knowledge
https://github.com/rongzhou7/ttt-unet
공식 코드TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation
https://github.com/root-ai/depth-quality
공식 코드Quantitative Depth Quality Assessment of RGBD Cameras At Close Range Using 3D Printed Fixtures
https://github.com/rosanajurdi/prior-based-losses-for-medical-image-segmentation
공식 코드Effect of Prior-based Losses on Segmentation Performance: A Benchmark
https://github.com/rowanz/neural-motifs
공식 코드https://github.com/rows21/dk-uxnet
공식 코드Semi-supervised Medical Image Segmentation via Query Distribution Consistency
https://github.com/rrrajjjj/flowgrad
공식 코드https://github.com/rstrudel/segmenter
공식 코드https://github.com/rt219/the-emergence-of-objectness
공식 코드The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
https://github.com/rtous/lester
공식 코드Lester: rotoscope animation through video object segmentation and tracking
https://github.com/rubics-xuan/fremim
공식 코드FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.