SOTAVerified

Object Detection

Papers

Showing 251275 of 10957 papers

TitleStatusHype
A DeNoising FPN With Transformer R-CNN for Tiny Object DetectionCode2
Parameter-Inverted Image Pyramid NetworksCode2
FedPylot: Navigating Federated Learning for Real-Time Object Detection in Internet of VehiclesCode2
GrootVL: Tree Topology is All You Need in State Space ModelCode2
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision TransformerCode2
Fully Test-Time Adaptation for Monocular 3D Object DetectionCode2
REACT: Real-time Efficiency and Accuracy Compromise for Tradeoffs in Scene Graph GenerationCode2
Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and BeyondCode2
DATR: Unsupervised Domain Adaptive Detection Transformer with Dataset-Level Adaptation and Prototypical AlignmentCode2
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch NormalizationCode2
DiverGen: Improving Instance Segmentation by Learning Wider Data Distribution with More Diverse Generative DataCode2
SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object DetectionCode2
SpecDETR: A Transformer-based Hyperspectral Point Object Detection NetworkCode2
Grounded 3D-LLM with Referent TokensCode2
GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNsCode2
ViewFormer: Exploring Spatiotemporal Modeling for Multi-View 3D Occupancy Perception via View-Guided TransformersCode2
PTQ4SAM: Post-Training Quantization for Segment AnythingCode2
CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather ConditionsCode2
Commonsense Prototype for Outdoor Unsupervised 3D Object DetectionCode2
ShadowRefiner: Towards Mask-free Shadow Removal via Fast Fourier TransformerCode2
MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image FusionCode2
SFSORT: Scene Features-based Simple Online Real-Time TrackerCode2
Scaling Multi-Camera 3D Object Detection through Weak-to-Strong ElicitingCode2
Learning Embeddings with Centroid Triplet Loss for Object Identification in Robotic GraspingCode2
YOLC: You Only Look Clusters for Tiny Object Detection in Aerial ImagesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Co-DETRbox mAP66Unverified
2InternImage-H (M3I Pre-training)box mAP65.5Unverified
3M3I Pre-training (InternImage-H)box mAP65.4Unverified
4MoCaEbox mAP65.1Unverified
5Co-DETR (Swin-L)box mAP64.8Unverified
6Focal-Stable-DINO (Focal-Huge, no TTA)box mAP64.8Unverified
7EVAbox mAP64.7Unverified
8Group DETR v2box mAP64.5Unverified
9FocalNet-H (DINO)box mAP64.4Unverified
10InternImage-XLbox mAP64.3Unverified