SOTAVerified

Pedestrian Detection

Pedestrian detection is the task of detecting pedestrians from a camera.

Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.

( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–50 of 438 papers

TitleStatusHype
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorsCode7
YOLOv6: A Single-Stage Object Detection Framework for Industrial ApplicationsCode5
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual TasksCode3
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark DatasetCode2
UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter TuningCode2
Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object DetectionCode2
Hulk: A Universal Knowledge Translator for Human-Centric TasksCode2
HumanBench: Towards General Human-centric Perception with Projector Assisted PretrainingCode2
CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with TransformersCode2
F2DNet: Fast Focal Detection Network for Pedestrian DetectionCode2
Pedestrian Detection: Domain Generalization, CNNs, Transformers and BeyondCode2
Detection in Crowded Scenes: One Proposal, Multiple PredictionsCode2
Focal Loss for Dense Object DetectionCode2
Feature Pyramid Networks for Object DetectionCode2
Fast Algorithms for Convolutional Neural NetworksCode2
Multispectral Pedestrian Detection with Sparsely Annotated LabelCode1
MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image FusionCode1
MambaST: A Plug-and-Play Cross-Spectral Spatial-Temporal Fuser for Efficient Pedestrian DetectionCode1
AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian DetectionCode1
MiPa: Mixed Patch Infrared-Visible Modality Agnostic Object DetectionCode1
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across EnvironmentsCode1
Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian DetectionCode1
INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian DetectionCode1
Paved2Paradise: Cost-Effective and Scalable LiDAR Simulation by Factoring the Real WorldCode1
DDAM-PS: Diligent Domain Adaptive Mixer for Person SearchCode1
HalluciDet: Hallucinating RGB Modality for Person Detection Through Privileged InformationCode1
Nonlinear optical encoding enabled by recurrent linear scatteringCode1
TFDet: Target-Aware Fusion for RGB-T Pedestrian DetectionCode1
CARLA-BSP: a simulated dataset with pedestriansCode1
VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-SupervisionCode1
UniHCP: A Unified Model for Human-Centric PerceptionsCode1
MS-DETR: Multispectral Pedestrian Detection Transformer with Loosely Coupled Fusion and Modality-Balanced OptimizationCode1
Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian DatasetCode1
Untargeted Backdoor Attack against Object DetectionCode1
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object DetectionCode1
LMOT: Efficient Light-Weight Detection and Tracking in CrowdsCode1
Domain Adaptive Person SearchCode1
3D Random Occlusion and Multi-Layer Projection for Deep Multi-Camera Pedestrian LocalizationCode1
PedRecNet: Multi-task deep neural network for full 3D human pose and orientation estimationCode1
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded ScenesCode1
Graph Neural Networks for Cross-Camera Data AssociationCode1
Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar NetworkCode1
Cross-Modality Fusion Transformer for Multispectral Object DetectionCode1
Bringing Generalization to Deep Multi-View Pedestrian DetectionCode1
LGD: Label-guided Self-distillation for Object DetectionCode1
Efficient and Effective Generation of Test Cases for Pedestrian Detection -- Search-based Software Testing of Baidu Apollo in SVLCode1
LLVIP: A Visible-infrared Paired Dataset for Low-light VisionCode1
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?Code1
BlockCopy: High-Resolution Video Processing with Block-Sparse Feature Propagation and Online PoliciesCode1
MLPD: Multi-Label Pedestrian Detector in Multispectral DomainCode1
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All datasetsCaltechCityPersonsLLVIPDVTODTJU-Ped-trafficTJU-Ped-campusCVC14Caltech Pedestrian DatasetMMPD-Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UniHCP (FT)Heavy MR^-227.2—Unverified
2LDCFReasonable Miss Rate24.8—Unverified
3AlexNetReasonable Miss Rate23.3—Unverified
4TA-CNNReasonable Miss Rate20.9—Unverified
5Checkerboards+Reasonable Miss Rate17.1—Unverified
6NNNFReasonable Miss Rate16.2—Unverified
7Part-level CNN + saliency and bounding box alignmentReasonable Miss Rate12.4—Unverified
8CompACT-DeepReasonable Miss Rate11.75—Unverified
9MCFReasonable Miss Rate10.4—Unverified
10MS-CNNReasonable Miss Rate9.95—Unverified
#ModelMetricClaimedVerifiedStatus
1ACSP + EuroCity PersonsHeavy MR^-242.5—Unverified
2TLLReasonable MR^-215.5—Unverified
3FRCNNReasonable MR^-215.4—Unverified
4FRCNN+SegReasonable MR^-214.8—Unverified
5TLL+MRFReasonable MR^-214.4—Unverified
6RepLossReasonable MR^-213.2—Unverified
7OR-CNNReasonable MR^-212.8—Unverified
8ALFNetReasonable MR^-212—Unverified
9CSP (with offset) + ResNet-50Reasonable MR^-211—Unverified
10NOH-NMSReasonable MR^-210.8—Unverified
#ModelMetricClaimedVerifiedStatus
1INSANetlog average miss rate4.43—Unverified
2MMPedestronAP0.73—Unverified
3CAFF-DINOAP0.69—Unverified
4CFTAP0.64—Unverified
5UniRGB-IRAP0.63—Unverified
6RSDetAP0.61—Unverified
7CMXAP0.6—Unverified
8CSSAAP0.59—Unverified
9GAFFAP0.56—Unverified
10Halfway FusionAP0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1YOLOv6 (Thermal) mAP84.4—Unverified
2CFT mAP82.7—Unverified
3YOLOv3 (Thermal) mAP82.7—Unverified
4CMX mAP81.6—Unverified
5YOLOv7 (Thermal)mAP77.8—Unverified
6YOLOv6 (Visible) mAP38.1—Unverified
7YOLOv7 (Visible)mAP35.3—Unverified
8YOLOv3 (Visible) mAP34.5—Unverified
#ModelMetricClaimedVerifiedStatus
1FCOSR (miss rate)24.35—Unverified
2RetinaNetR (miss rate)23.89—Unverified
3FPNR (miss rate)22.3—Unverified
4CrowdDetR (miss rate)20.82—Unverified
5EGCLR (miss rate)19.73—Unverified
6LSFMR (miss rate)18.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RetinaNetR (miss rate)34.73—Unverified
2FCOSR (miss rate)31.89—Unverified
3CrowdDetR (miss rate)25.73—Unverified
4EGCLR (miss rate)24.84—Unverified
#ModelMetricClaimedVerifiedStatus
1CFTAP5078.2—Unverified
2CMXAP5068.9—Unverified
#ModelMetricClaimedVerifiedStatus
1LSFMMR0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1MMPedestronbox mAP79—Unverified