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SOTA
Objekterkennung
Object Detection On Pascal Voc 2007
Object Detection On Pascal Voc 2007
Metriken
MAP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
MAP
Paper Title
Cascade Eff-B7 NAS-FPN (Copy Paste pre-training, single-scale)
89.3%
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation
YOLO-Former
86.01%
YOLO-Former: YOLO Shakes Hand With ViT
DETReg (MDef-DETR)
84.16%
Class-agnostic Object Detection with Multi-modal Transformer
HSD (VGG16, 512x512, single-scale test)
83.0%
Hierarchical Shot Detector
CoupleNet
82.7%
CoupleNet: Coupling Global Structure with Local Parts for Object Detection
EEEA-Net-C2 (YOLOv4)
81.8%
EEEA-Net: An Early Exit Evolutionary Neural Architecture Search
HSD (VGG16, 320x320, single-scale test)
81.7%
Hierarchical Shot Detector
SSD512 (07+12+COCO)
81.6%
SSD: Single Shot MultiBox Detector
BlitzNet512 + seg (s8)
81.5%
BlitzNet: A Real-Time Deep Network for Scene Understanding
Localize
81.5%
Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection
CenterNet(DLA34, Flip, 512x512)
80.7%
Objects as Points
PS-KD (ResNet-152, CutMix)
79.7%
Self-Knowledge Distillation with Progressive Refinement of Targets
DPNet
79.2%
DPNet: Dual-Path Network for Real-time Object Detection with Lightweight Attention
OHEM
78.9%
Training Region-based Object Detectors with Online Hard Example Mining
YOLO v2
78.6%
YOLO9000: Better, Faster, Stronger
ThunderNet SNet535 Backbone
78.6%
ThunderNet: Towards Real-time Generic Object Detection
DeNet-101 (skip)
77.1%
DeNet: Scalable Real-time Object Detection with Directed Sparse Sampling
I+ORE
76.2%
Random Erasing Data Augmentation
Perona Malik (Perona and Malik, 1990)
74.37%
Learning Visual Representations for Transfer Learning by Suppressing Texture
FRCN
74.2%
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection
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Object Detection On Pascal Voc 2007 | SOTA | HyperAI