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Semantic Segmentation

Papers

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Showing 1026–1050 of 14763 papers

TitleStatusHype
AutoFish: Dataset and Benchmark for Fine-grained Analysis of Fish—0
CFFormer: Cross CNN-Transformer Channel Attention and Spatial Feature Fusion for Improved Segmentation of Low Quality Medical Images—0
LM-Net: A Light-weight and Multi-scale Network for Medical Image SegmentationCode1
VOILA: Complexity-Aware Universal Segmentation of CT images by Voxel Interacting with LanguageCode0
Image Segmentation: Inducing graph-based learningCode0
Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images—0
DGSSA: Domain generalization with structural and stylistic augmentation for retinal vessel segmentation—0
SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation—0
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and VideosCode5
The 2nd Place Solution from the 3D Semantic Segmentation Track in the 2024 Waymo Open Dataset Challenge—0
A Novel Vision Transformer for Camera-LiDAR Fusion based Traffic Object Segmentation—0
Comprehensive Pathological Image Segmentation via Teacher Aggregation for Tumor Microenvironment Analysis—0
AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image SegmentationCode1
Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation—0
PARF-Net: integrating pixel-wise adaptive receptive fields into hybrid Transformer-CNN network for medical image segmentation—0
GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image SegmentationCode0
4D-CS: Exploiting Cluster Prior for 4D Spatio-Temporal LiDAR Semantic SegmentationCode0
KM-UNet KAN Mamba UNet for medical image segmentationCode1
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation—0
Framework for lung CT image segmentation based on UNet++—0
Unsupervised Class Generation to Expand Semantic Segmentation Datasets—0
tCURLoRA: Tensor CUR Decomposition Based Low-Rank Parameter Adaptation and Its Application in Medical Image Segmentation—0
Tree-NET: Enhancing Medical Image Segmentation Through Efficient Low-Level Feature Training—0
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
Dedicated Inference Engine and Binary-Weight Neural Networks for Lightweight Instance Segmentation—0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
5InternImage-HValidation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified