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Semantic Segmentation

Papers

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Showing 4526–4550 of 14763 papers

TitleStatusHype
Beyond Single Stage Encoder-Decoder Networks: Deep Decoders for Semantic Image Segmentation—0
An Abstraction Model for Semantic Segmentation Algorithms—0
Demonstrating Multi-Suction Item Picking at Scale via Multi-Modal Learning of Pick Success—0
Focus on Your Target: A Dual Teacher-Student Framework for Domain-adaptive Semantic Segmentation—0
Derivate-based Component-Trees for Multi-Channel Image Segmentation—0
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread—0
Beyond Semantic Image Segmentation : Exploring Efficient Inference in Video—0
Depth-wise layering of 3d images using dense depth maps: a threshold based approach—0
Depth-SIMS: Semi-Parametric Image and Depth Synthesis—0
Depth-Sensitive Soft Suppression with RGB-D Inter-Modal Stylization Flow for Domain Generalization Semantic Segmentation—0
AMVNet: Assertion-based Multi-View Fusion Network for LiDAR Semantic Segmentation—0
Deep Neural Networks for Surface Segmentation Meet Conditional Random Fields—0
DepthSeg: Depth prompting in remote sensing semantic segmentation—0
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network—0
A Multi-threshold Segmentation Approach Based on Artificial Bee Colony Optimization—0
Depth Matters: Exploring Deep Interactions of RGB-D for Semantic Segmentation in Traffic Scenes—0
DepthMatch: Semi-Supervised RGB-D Scene Parsing through Depth-Guided Regularization—0
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields—0
Sketch2code: Generating a website from a paper mockup—0
Depth-guided Texture Diffusion for Image Semantic Segmentation—0
Depth-Guided Semi-Supervised Instance Segmentation—0
Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics—0
DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networks—0
Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models—0
A multi-task U-net for segmentation with lazy labels—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
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation 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