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Semantic Segmentation

Papers

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Showing 4501–4525 of 14763 papers

TitleStatusHype
Flow 2.0 -a flexible, scalable, cross-platform post-processing software for realtime phase contrast sequences—0
Detangling People: Individuating Multiple Close People and Their Body Parts via Region Assembly—0
Detailed Evaluation of Modern Machine Learning Approaches for Optic Plastics Sorting—0
BFS-Net: Weakly Supervised Cell Instance Segmentation from Bright-Field Microscopy Z-Stacks—0
Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform—0
DesnowNet: Context-Aware Deep Network for Snow Removal—0
An Accurate Texture Complexity Estimation for Quality-Enhanced and Secure Image Steganography—0
Design Pseudo Ground Truth with Motion Cue for Unsupervised Video Object Segmentation—0
Design of Real-time Semantic Segmentation Decoder for Automated Driving—0
BezierSeg: Parametric Shape Representation for Fast Object Segmentation in Medical Images—0
Designing DNNs for a trade-off between robustness and processing performance in embedded devices—0
Be Your Own Prada: Fashion Synthesis with Structural Coherence—0
An Access Control Method with Secret Key for Semantic Segmentation Models—0
Adapting Segment Anything Model to Melanoma Segmentation in Microscopy Slide Images—0
Design equivariant neural networks for 3D point cloud—0
DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images—0
Deshadow-Anything: When Segment Anything Model Meets Zero-shot shadow removal—0
Beyond the Final Layer: Hierarchical Query Fusion Transformer with Agent-Interpolation Initialization for 3D Instance Segmentation—0
Descriptor-Free Multi-View Region Matching for Instance-Wise 3D Reconstruction—0
Descriptive Modeling of Textiles using FE Simulations and Deep Learning—0
DESC: Domain Adaptation for Depth Estimation via Semantic Consistency—0
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
Flow Based Self-supervised Pixel Embedding for Image 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
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