SOTAVerified

Few-Shot Object Detection

Few-Shot Object Detection is a computer vision task that involves detecting objects in images with limited training data. The goal is to train a model on a few examples of each object class and then use the model to detect objects in new images.

Papers

Showing 101150 of 179 papers

TitleStatusHype
Few-Shot Object Detection in Unseen Domains0
Few-Shot Object Detection with Fully Cross-TransformerCode1
Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison0
Sylph: A Hypernetwork Framework for Incremental Few-shot Object DetectionCode1
Efficient Few-Shot Object Detection via Knowledge InheritanceCode1
UnseenNet: Fast Training Detector for Any Unseen ConceptCode0
Mobile Robot Manipulation using Pure Object DetectionCode1
A Unified Framework for Attention-Based Few-Shot Object Detection0
Kernelized Few-Shot Object Detection With Efficient Integral Aggregation0
Few-Shot Object Detection: A Comprehensive Survey0
Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional NetworksCode1
Label, Verify, Correct: A Simple Few Shot Object Detection MethodCode1
Grounded Language-Image Pre-trainingCode2
A Survey of Deep Learning for Low-Shot Object Detection0
AirDet: Few-Shot Detection without Fine-tuning for Autonomous ExplorationCode1
Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary EnhancementCode1
Few-Shot Object Detection via Association and DIscriminationCode1
Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object DetectionCode1
A Comparative Review of Recent Few-Shot Object Detection Algorithms0
Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection0
A Survey of Self-Supervised and Few-Shot Object DetectionCode1
Instant Response Few-shot Object Detection with Meta Strategy and Explicit Localization InferenceCode0
MDFL: A UNIFIED FRAMEWORK WITH META-DROPOUT FOR FEW-SHOT LEARNING0
Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial ImagesCode0
Towards Generalized and Incremental Few-Shot Object Detection0
Few-Shot Object Detection by Attending to Per-Sample-Prototype0
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object DetectionCode1
Dynamic Relevance Learning for Few-Shot Object DetectionCode1
Towards Accurate Localization by Instance Search0
Transformation Invariant Few-Shot Object Detection0
Few-Shot Object Detection via Classification Refinement and Distractor Retreatment0
Accurate Few-Shot Object Detection With Support-Query Mutual Guidance and Hybrid Loss0
DETReg: Unsupervised Pretraining with Region Priors for Object DetectionCode1
Generalized Few-Shot Object Detection without ForgettingCode1
Class-Incremental Few-Shot Object Detection0
Hallucination Improves Few-Shot Object Detection0
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature AlignmentCode1
Dense Relation Distillation with Context-aware Aggregation for Few-Shot Object DetectionCode1
Meta-DETR: Image-Level Few-Shot Object Detection with Inter-Class Correlation ExploitationCode1
FSCE: Few-Shot Object Detection via Contrastive Proposal EncodingCode1
Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object DetectionCode1
Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection0
Universal-Prototype Enhancing for Few-Shot Object DetectionCode1
Dual-Awareness Attention for Few-Shot Object DetectionCode1
Few-Shot Learning for Road Object Detection0
MM-FSOD: Meta and metric integrated few-shot object detection0
AFD-Net: Adaptive Fully-Dual Network for Few-Shot Object Detection0
Cooperating RPN's Improve Few-Shot Object Detection0
Few-Shot Object Detection in Real Life: Case Study on Auto-Harvest0
Restoring Negative Information in Few-Shot Object DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Training-freeAP36.6Unverified
2CD-ViTOAP35.3Unverified
3DE-ViTAP34Unverified
4BIOTAP26.3Unverified
5RISF (SWIN-Large)AP25.5Unverified
6DETReg-ft-full DDETRAP25Unverified
7imTED+ViT-BAP22.5Unverified
8hANMCLAP22.4Unverified
9RISF (Resnet-101)AP21.9Unverified
10DCFSAP19.5Unverified
#ModelMetricClaimedVerifiedStatus
1FS-CDIS (iFS-RCNN+ITL 5-shot)box AP10.36Unverified
2FS-CDIS (MTFA+IMS 5-shot)box AP10.36Unverified
3FS-CDIS (Res101-MTFA+IMS 5-shot)box AP10.36Unverified
4FS-CDIS (Res101-MTFA+ITL 5-shot)box AP9.76Unverified
5FS-CDIS (M-RCNN+ITL 5-shot)box AP9.67Unverified
6FS-CDIS (M-RCNN+IMS 5-shot)box AP9.52Unverified
7FS-CDIS (iFS-RCNN+IMS 5-shot)box AP8.44Unverified
8FS-CDIS (M-RCNN+IMS 3-shot)box AP7.96Unverified
9FS-CDIS (M-RCNN+ITL 3-shot)box AP7.85Unverified
10FS-CDIS (M-RCNN+ITL 2-shot)box AP7.56Unverified
#ModelMetricClaimedVerifiedStatus
1Training-freeAP36.8Unverified
2CD-ViTOAP35.9Unverified
3DE-ViTAP34Unverified
4BIOTAP33.8Unverified
5RISF (SWIN-Large)AP31.9Unverified
6imTED+ViT-BAP30.2Unverified
7DETReg-ft-full DDETRAP30Unverified
8hANMCLAP25Unverified
9RISF (Resnet-101)AP24.4Unverified
10Meta-DETR (Multi-Scale Feature)AP22.9Unverified
#ModelMetricClaimedVerifiedStatus
1best_single_model_valAP47.55Unverified
2htcAP39.05Unverified
3Organizer Provided BaselineAP27.26Unverified
4nullAP25.8Unverified
5Forest R-CNNAP23.2Unverified
6personAP21.82Unverified
7test balloon 6AP16.62Unverified
#ModelMetricClaimedVerifiedStatus
1Training-freeAP26.5Unverified
2hANMCLAP13.4Unverified
3UniFSAP12.7Unverified
4RISFAP11.7Unverified
5DCFSAP10Unverified
6DeFRCNAP9.3Unverified
7DCFSAP8.1Unverified
#ModelMetricClaimedVerifiedStatus
1TestConsistencyAP48.58Unverified
2ps4AP39.67Unverified
3Asynchronous SSLAP37.72Unverified
4CenterNet2AP35.84Unverified
5Organizer Provided BaselineAP26.86Unverified
#ModelMetricClaimedVerifiedStatus
1Grounding DINO 1.5 ProAverage Score66.3Unverified
2MQ-GLIP-TAverage Score57Unverified
3GLIP-TAverage Score50.7Unverified
#ModelMetricClaimedVerifiedStatus
1Grounding DINO 1.5 ProAverage Score54.7Unverified
2MQ-GLIP-TAverage Score43Unverified
3GLIP-TAverage Score38.9Unverified
#ModelMetricClaimedVerifiedStatus
1DETReg (ours)AP30Unverified
#ModelMetricClaimedVerifiedStatus
1UniFSAP18.2Unverified