Video Object Detection
71 papers with code • 8 benchmarks • 12 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Video Object Detection
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Libraries
Use these libraries to find Video Object Detection models and implementationsDatasets
Waymo Open Dataset
EPIC-KITCHENS-55
ImageNet VID
YT-BB
OAK
Underwater Trash Detection
THGP
Most implemented papers
Emerging Properties in Self-Supervised Vision Transformers
facebookresearch/dino
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ICCV 2021
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets).
TSM: Temporal Shift Module for Efficient Video Understanding
MIT-HAN-LAB/temporal-shift-module
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ICCV 2019
The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost.
Mobile Video Object Detection with Temporally-Aware Feature Maps
tensorflow/models
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CVPR 2018
This paper introduces an online model for object detection in videos designed to run in real-time on low-powered mobile and embedded devices.
Towards High Performance Video Object Detection for Mobiles
stanlee321/LightFlow-TensorFlow
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In this paper, we present a light weight network architecture for video object detection on mobiles.
Transferable Adversarial Attacks for Image and Video Object Detection
LiangSiyuan21/Adversarial-Attacks-for-Image-and-Video-Object-Detection
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Adversarial examples have been demonstrated to threaten many computer vision tasks including object detection.
Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection
tensorflow/models
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CVPR 2020
In this paper we propose a method that leverages temporal context from the unlabeled frames of a novel camera to improve performance at that camera.
HoughNet: Integrating near and long-range evidence for visual detection
This paper presents HoughNet, a one-stage, anchor-free, voting-based, bottom-up object detection method.
TransVOD: End-to-End Video Object Detection with Spatial-Temporal Transformers
Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous complex hand-crafted detectors.
Flow-Guided Feature Aggregation for Video Object Detection
msracver/Flow-Guided-Feature-Aggregation
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ICCV 2017
The accuracy of detection suffers from degenerated object appearances in videos, e. g., motion blur, video defocus, rare poses, etc.
Looking Fast and Slow: Memory-Guided Mobile Video Object Detection
Models and examples built with TensorFlow
