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Video Object Detection

15 papers with code ยท Computer Vision
Subtask of 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 )

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Latest papers without code

Memory Enhanced Global-Local Aggregation for Video Object Detection

CVPR 2020

We argue that there are two important cues for humans to recognize objects in videos: the global semantic information and the local localization information.

VIDEO OBJECT DETECTION

Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection

CVPR 2020

Weakly supervised learning has emerged as a compelling tool for object detection by reducing the need for strong supervision during training.

VIDEO OBJECT DETECTION WEAKLY SUPERVISED OBJECT DETECTION

LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention

CVPR 2020

In this paper, we propose an end-to-end online 3D video object detector that operates on point cloud sequences.

VIDEO OBJECT DETECTION

Plug & Play Convolutional Regression Tracker for Video Object Detection

2 Mar 2020

As the tracker reuses the features from the detector, it is a very light-weighted increment to the detection network.

VIDEO OBJECT DETECTION

Rethinking Temporal Object Detection from Robotic Perspectives

22 Dec 2019

From a robotic perspective, the importance of recall continuity and localization stability is equal to that of accuracy, but the AP is insufficient to reflect detectors' performance across time.

MULTI-OBJECT TRACKING VIDEO OBJECT DETECTION

Learning Motion Priors for Efficient Video Object Detection

13 Nov 2019

Recently, image-level flow warping has been proposed to propagate features across different frames, aiming at achieving a better trade-off between accuracy and efficiency.

OPTICAL FLOW ESTIMATION VIDEO OBJECT DETECTION

A Delay Metric for Video Object Detection: What Average Precision Fails to Tell

ICCV 2019

Average precision (AP) is a widely used metric to evaluate detection accuracy of image and video object detectors.

VIDEO OBJECT DETECTION

Progressive Sparse Local Attention for Video Object Detection

ICCV 2019

Instead of relying on optical flow, this paper proposes a novel module called Progressive Sparse Local Attention (PSLA), which establishes the spatial correspondence between features across frames in a local region with progressively sparser stride and uses the correspondence to propagate features.

OPTICAL FLOW ESTIMATION VIDEO OBJECT DETECTION