SOTAVerified

Instance Segmentation

Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.

Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21

Papers

Showing 19261950 of 2262 papers

TitleStatusHype
COIN: Confidence Score-Guided Distillation for Annotation-Free Cell SegmentationCode0
Unsupervised object-centric video generation and decomposition in 3DCode0
Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple ObjectsCode0
ICDAR 2021 Competition on Historical Map SegmentationCode0
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
How Shift Equivariance Impacts Metric Learning for Instance SegmentationCode0
Weakly Supervised Instance Segmentation using Class Peak ResponseCode0
Horticultural Temporal Fruit Monitoring via 3D Instance Segmentation and Re-Identification using Point CloudsCode0
HistoNet: Predicting size histograms of object instancesCode0
Surgical fine-tuning for Grape Bunch Segmentation under Visual Domain ShiftsCode0
Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance SegmentationCode0
Hiera: A Hierarchical Vision Transformer without the Bells-and-WhistlesCode0
Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing ImageryCode0
Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual RepresentationsCode0
HaDR: Applying Domain Randomization for Generating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial EnvironmentsCode0
Actor-Critic Instance SegmentationCode0
GRAtt-VIS: Gated Residual Attention for Auto Rectifying Video Instance SegmentationCode0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
Grape detection, segmentation and tracking using deep neural networks and three-dimensional associationCode0
CoDA: Interactive Segmentation and Morphological Analysis of Dendroid Structures Exemplified on Stony Cold-Water CoralsCode0
Gramian Attention Heads are Strong yet Efficient Vision LearnersCode0
Weakly Supervised Instance Segmentation using the Bounding Box Tightness PriorCode0
Weakly-supervised Instance Segmentation via Class-agnostic Learning with Salient ImagesCode0
GMT: Guided Mask Transformer for Leaf Instance SegmentationCode0
UPSNet: A Unified Panoptic Segmentation NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-HAP5080.8Unverified
2ResNeSt-200 (multi-scale)AP5070.2Unverified
3CenterMask + VoVNetV2-99 (multi-scale)AP5066.2Unverified
4CenterMask + VoVNetV2-57 (single-scale)AP5060.8Unverified
5Co-DETRmask AP57.1Unverified
6CBNetV2 (EVA02, single-scale)mask AP56.1Unverified
7ISDA (ResNet-50)APL55.7Unverified
8EVAmask AP55.5Unverified
9FD-SwinV2-Gmask AP55.4Unverified
10Mask Frozen-DETRmask AP55.3Unverified
#ModelMetricClaimedVerifiedStatus
1InternImage-BGFLOPs501Unverified
2Co-DETRmask AP56.6Unverified
3ViT-CoMer-L (Mask RCNN, DINOv2)mask AP55.9Unverified
4InternImage-Hmask AP55.4Unverified
5EVAmask AP55Unverified
6Mask Frozen-DETRmask AP54.9Unverified
7MasK DINO (SwinL, multi-scale)mask AP54.5Unverified
8ViT-Adapter-L (HTC++, BEiTv2, O365, multi-scale)mask AP54.2Unverified
9GLEE-Promask AP54.2Unverified
10SwinV2-G (HTC++)mask AP53.7Unverified