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Semantic Segmentation

Papers

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Showing 7801–7850 of 14763 papers

TitleStatusHype
Combining Implicit-Explicit View Correlation for Light Field Semantic Segmentation—0
A Semantic-aware Attention and Visual Shielding Network for Cloth-changing Person Re-identification—0
Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentation—0
Few-shot image segmentation for cross-institution male pelvic organs using registration-assisted prototypical learning—0
Accurate and efficient zero-shot 6D pose estimation with frozen foundation models—0
Live-wire 3D medical images segmentation—0
MILAN: Milli-Annotations for Lidar Semantic Segmentation—0
Adversarial normalization for multi domain image segmentation—0
MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation—0
Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classification—0
LKASeg:Remote-Sensing Image Semantic Segmentation with Large Kernel Attention and Full-Scale Skip Connections—0
MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images—0
LlamaSeg: Image Segmentation via Autoregressive Mask Generation—0
Mind The Gap: Alleviating Local Imbalance for Unsupervised Cross-Modality Medical Image Segmentation—0
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks—0
Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation—0
LLM-Guided Taxonomy and Hierarchical Uncertainty for 3D Point CLoud Active Learning—0
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification—0
Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition—0
LMFNet: An Efficient Multimodal Fusion Approach for Semantic Segmentation in High-Resolution Remote Sensing—0
Few-shot adaptation for morphology-independent cell instance segmentation—0
LMSeg: A deep graph message-passing network for efficient and accurate semantic segmentation of large-scale 3D landscape meshes—0
Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network—0
Few-Shot 3D Volumetric Segmentation with Multi-Surrogate Fusion—0
Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network—0
Local Context Attention for Salient Object Segmentation—0
Combining Bottom-Up, Top-Down, and Smoothness Cues for Weakly Supervised Image Segmentation—0
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation—0
Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation—0
Local-Global Pseudo-label Correction for Source-free Domain Adaptive Medical Image Segmentation—0
3D Face Reconstruction Using Color Photometric Stereo with Uncalibrated Near Point Lights—0
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving—0
Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation—0
Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation—0
Few Exemplar-Based General Medical Image Segmentation via Domain-Aware Selective Adaptation—0
Localization and Expansion: A Decoupled Framework for Point Cloud Few-shot Semantic Segmentation—0
Differentiable Spline Approximations—0
Localized Feature Aggregation Module for Semantic Segmentation—0
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation—0
Combined Approach for Image Segmentation—0
A Self-Supervised Method for Body Part Segmentation and Keypoint Detection of Rat Images—0
Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation—0
Few Clicks Suffice: Active Test-Time Adaptation for Semantic Segmentation—0
Localizing Adverts in Outdoor Scenes—0
DiffMap: Enhancing Map Segmentation with Map Prior Using Diffusion Model—0
Locally Adaptive Learning Loss for Semantic Image Segmentation—0
FE-UNet: Frequency Domain Enhanced U-Net with Segment Anything Capability for Versatile Image Segmentation—0
BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks—0
Combinatorial Energy Learning for Image Segmentation—0
Adversarial Networks for the Detection of Aggressive Prostate Cancer—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