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Video Object Detection

Video object detection is the task of detecting objects from a video as opposed to images.

( Image credit: Learning Motion Priors for Efficient Video Object Detection )

Papers

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Showing 76–100 of 147 papers

TitleStatusHype
Spatio-Temporal Learnable Proposals for End-to-End Video Object Detection—0
DFA: Dynamic Feature Aggregation for Efficient Video Object Detection—0
DAFA: Diversity-Aware Feature Aggregation for Attention-Based Video Object Detection—0
TemporalNet: Real-time 2D-3D Video Object Detection—0
Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks—0
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds—0
QueryProp: Object Query Propagation for High-Performance Video Object DetectionCode0
Exploring Temporally Dynamic Data Augmentation for Video Recognition—0
Representation Recycling for Streaming Video AnalysisCode0
Single Object Tracking Research: A Survey—0
SALISA: Saliency-based Input Sampling for Efficient Video Object Detection—0
Delta Distillation for Efficient Video ProcessingCode0
SmartAdapt: Multi-Branch Object Detection Framework for Videos on Mobiles—0
Virtuoso: Video-based Intelligence for real-time tuning on SOCs—0
SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation—0
Temporal RoI Align for Video Object Recognition—0
Temporal Early Exits for Efficient Video Object Detection—0
SGE net: Video object detection with squeezed GRU and information entropy map—0
When Few-Shot Learning Meets Video Object Detection—0
New Generation Deep Learning For Video Object Dection:A Survery—0
Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving—0
An Analysis of Deep Object Detectors For Diver Detection—0
Joint Representation of Temporal Image Sequences and Object Motion for Video Object DetectionCode0
Recurrent Neural Networks for video object detection—0
Object-aware Feature Aggregation for Video Object Detection—0
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