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Semantic Segmentation

Papers

Showing 326350 of 14763 papers

TitleStatusHype
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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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310Unverified
2ViT-P (InternImage-H)Validation mIoU63.6Unverified
3ONE-PEACEValidation mIoU63Unverified
4M3I Pre-training (InternImage-H)Validation mIoU62.9Unverified
5InternImage-HValidation mIoU62.9Unverified
6BEiT-3Validation mIoU62.8Unverified
7EVAValidation mIoU62.3Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5Unverified
10FD-SwinV2-GValidation mIoU61.4Unverified