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Semantic Segmentation

Papers

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Showing 7351–7400 of 14763 papers

TitleStatusHype
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search—0
SCIM: Simultaneous Clustering, Inference, and Mapping for Open-World Semantic Scene UnderstandingCode0
Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency—0
Using the Polar Transform for Efficient Deep Learning-Based Aorta Segmentation in CTA ImagesCode1
LargeKernel3D: Scaling up Kernels in 3D Sparse CNNsCode2
Semantics-Depth-Symbiosis: Deeply Coupled Semi-Supervised Learning of Semantics and Depth—0
SemMAE: Semantic-Guided Masking for Learning Masked AutoencodersCode1
Review Neural Networks about Image Transformation Based on IGC Learning Framework with Annotated Information—0
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision ApplicationsCode2
LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation—0
Broken News: Making Newspapers Accessible to Print-Impaired—0
Distribution Regularized Self-Supervised Learning for Domain Adaptation of Semantic Segmentation—0
Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic SegmentationCode0
Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers—0
Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy AutoencodersCode2
What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation—0
MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot SegmentationCode1
ORFD: A Dataset and Benchmark for Off-Road Freespace DetectionCode2
Global Context Vision TransformersCode2
Distortion-Aware Network Pruning and Feature Reuse for Real-time Video Segmentation—0
5th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation—0
0/1 Deep Neural Networks via Block Coordinate Descent—0
Deep Compatible Learning for Partially-Supervised Medical Image Segmentation—0
3D Face Parsing via Surface Parameterization and 2D Semantic Segmentation Network—0
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image SegmentationCode1
REVECA -- Rich Encoder-decoder framework for Video Event CAptionerCode1
Diffusion models as plug-and-play priorsCode2
DenseMTL: Cross-task Attention Mechanism for Dense Multi-task LearningCode1
Learning Implicit Feature Alignment Function for Semantic SegmentationCode1
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image ProcessingCode0
On Efficient Real-Time Semantic Segmentation: A Survey—0
Patch-level Representation Learning for Self-supervised Vision TransformersCode1
Simple and Efficient Architectures for Semantic SegmentationCode1
Online Segmentation of LiDAR Sequences: Dataset and AlgorithmCode1
Volumetric Supervised Contrastive Learning for Seismic Semantic Segmentation—0
Balancing Discriminability and Transferability for Source-Free Domain AdaptationCode1
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image SegmentationCode1
Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy LabelsCode1
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation—0
Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin & Eosin-Stained Histological Images—0
CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation—0
A Unified Sequence Interface for Vision Tasks—0
How to Reduce Change Detection to Semantic SegmentationCode1
Masked Frequency Modeling for Self-Supervised Visual Pre-TrainingCode1
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
SAVi++: Towards End-to-End Object-Centric Learning from Real-World VideosCode1
Real3D-Aug: Point Cloud Augmentation by Placing Real Objects with Occlusion Handling for 3D Detection and SegmentationCode1
S^2-FPN: Scale-ware Strip Attention Guided Feature Pyramid Network for Real-time Semantic SegmentationCode1
Data-Driven Deep Supervision for Medical Image Segmentation—0
Confidence-Guided Unsupervised Domain Adaptation for Cerebellum 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