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Semantic Segmentation

Papers

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Showing 301–350 of 14763 papers

TitleStatusHype
MogaNet: Multi-order Gated Aggregation NetworkCode2
StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic SegmentationCode2
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene ImageryCode2
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object SegmentationCode2
FastInst: A Simple Query-Based Model for Real-Time Instance SegmentationCode2
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and TransformerCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision ApplicationsCode2
E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance SegmentationCode2
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT AdaptationCode2
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic SegmentationCode2
Efficient 3D Semantic Segmentation with Superpoint TransformerCode2
DreamLIP: Language-Image Pre-training with Long CaptionsCode2
Domain Adaptation with a Single Vision-Language EmbeddingCode2
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationCode2
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative DataCode2
Distribution-Free, Risk-Controlling Prediction SetsCode2
Diversified and Personalized Multi-rater Medical Image SegmentationCode2
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic SegmentationCode2
Visible-Thermal Multiple Object Tracking: Large-scale Video Dataset and Progressive Fusion ApproachCode2
AllWeatherNet:Unified Image Enhancement for Autonomous Driving under Adverse Weather and Lowlight-conditionsCode2
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale DatasetCode2
Ambiguous Medical Image Segmentation using Diffusion ModelsCode2
Does Image Anonymization Impact Computer Vision Training?Code2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
DreamColour: Controllable Video Colour Editing without TrainingCode2
DuPL: Dual Student with Trustworthy Progressive Learning for Robust Weakly Supervised Semantic SegmentationCode2
Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object SegmentationCode2
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic SegmentationCode2
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic EnvironmentsCode2
A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and BenchmarkCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt TuningCode2
Fast Vision Transformers with HiLo AttentionCode2
An End-to-End Robust Point Cloud Semantic Segmentation Network with Single-Step Conditional Diffusion ModelsCode2
Generative Active Learning for Long-tailed Instance SegmentationCode2
Diffusion models as plug-and-play priorsCode2
Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable DiffusionCode2
DiffBEV: Conditional Diffusion Model for Bird's Eye View PerceptionCode2
An Empirical Study of Remote Sensing PretrainingCode2
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask DiffusionCode2
EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-SupervisionCode2
MobileOne: An Improved One millisecond Mobile BackboneCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
Exact: Exploring Space-Time Perceptive Clues for Weakly Supervised Satellite Image Time Series Semantic SegmentationCode2
Exploring CLIP's Dense Knowledge for Weakly Supervised Semantic SegmentationCode2
Digital Twin Generation from Visual Data: A SurveyCode2
DFormer: Rethinking RGBD Representation Learning for Semantic SegmentationCode2
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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