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Semantic Segmentation

Papers

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Showing 151–200 of 14763 papers

TitleStatusHype
Breaking reCAPTCHAv2Code3
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic ModelCode3
5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition TasksCode3
Merlin: A Vision Language Foundation Model for 3D Computed TomographyCode3
Anything-3D: Towards Single-view Anything Reconstruction in the WildCode3
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous DrivingCode3
Exploring Regional Clues in CLIP for Zero-Shot Semantic SegmentationCode3
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image SegmentationCode3
FastViT: A Fast Hybrid Vision Transformer using Structural ReparameterizationCode3
PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360degCode3
FRACTAL: An Ultra-Large-Scale Aerial Lidar Dataset for 3D Semantic Segmentation of Diverse LandscapesCode3
Personalize Segment Anything Model with One ShotCode3
Interactive Medical Image Segmentation: A Benchmark Dataset and BaselineCode3
Point Transformer V3: Simpler, Faster, StrongerCode3
Transformers in Medical Imaging: A SurveyCode3
CM-UNet: Hybrid CNN-Mamba UNet for Remote Sensing Image Semantic SegmentationCode3
RAP-SAM: Towards Real-Time All-Purpose Segment AnythingCode3
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature TransformCode3
MogaNet: Multi-order Gated Aggregation NetworkCode2
Ambiguous Medical Image Segmentation using Diffusion ModelsCode2
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
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and TransformerCode2
ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt TuningCode2
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision ApplicationsCode2
AllWeatherNet:Unified Image Enhancement for Autonomous Driving under Adverse Weather and Lowlight-conditionsCode2
EasyPortrait -- Face Parsing and Portrait Segmentation DatasetCode2
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural NetworksCode2
Efficient 3D Semantic Segmentation with Superpoint TransformerCode2
Alleviating Textual Reliance in Medical Language-guided Segmentation via Prototype-driven Semantic ApproximationCode2
DytanVO: Joint Refinement of Visual Odometry and Motion Segmentation in Dynamic EnvironmentsCode2
E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance SegmentationCode2
Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object SegmentationCode2
DuPL: Dual Student with Trustworthy Progressive Learning for Robust Weakly Supervised Semantic SegmentationCode2
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT AdaptationCode2
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic SegmentationCode2
DreamColour: Controllable Video Colour Editing without TrainingCode2
DreamLIP: Language-Image Pre-training with Long CaptionsCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic SegmentationCode2
Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image SegmentationCode2
DSNet: A Novel Way to Use Atrous Convolutions in Semantic SegmentationCode2
Earth-Adapter: Bridge the Geospatial Domain Gaps with Mixture of Frequency AdaptationCode2
Efficient Video Object Segmentation via Modulated Cross-Attention MemoryCode2
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
AiTLAS: Artificial Intelligence Toolbox for Earth ObservationCode2
1st Place Solution for PSG competition with ECCV'22 SenseHuman WorkshopCode2
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale DatasetCode2
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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