Video Object Detection
66 papers with code • 7 benchmarks • 10 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
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Video Object Detection models and implementationsDatasets
Waymo Open Dataset
EPIC-KITCHENS-55
ImageNet VID
YT-BB
OAK
THGP
VISEM-Tracking
Latest papers with no code
Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds
In this paper, we propose to detect 3D objects by exploiting temporal information in multiple frames, i. e., the point cloud videos.
QueryProp: Object Query Propagation for High-Performance Video Object Detection
The proposed QueryProp contains two propagation strategies: 1) query propagation is performed from sparse key frames to dense non-key frames to reduce the redundant computation on non-key frames; 2) query propagation is performed from previous key frames to the current key frame to improve feature representation by temporal context modeling.
Exploring Temporally Dynamic Data Augmentation for Video Recognition
The magnitude of augmentation operations on each frame is changed by an effective mechanism, Fourier Sampling that parameterizes diverse, smooth, and realistic temporal variations.
Single Object Tracking Research: A Survey
Visual object tracking is an important task in computer vision, which has many real-world applications, e. g., video surveillance, visual navigation.
SALISA: Saliency-based Input Sampling for Efficient Video Object Detection
In this paper, we propose SALISA, a novel non-uniform SALiency-based Input SAmpling technique for video object detection that allows for heavy down-sampling of unimportant background regions while preserving the fine-grained details of a high-resolution image.
SmartAdapt: Multi-Branch Object Detection Framework for Videos on Mobiles
In this paper, we ask, and answer, the wide-ranging question across all MBODFs: How to expose the right set of execution branches and then how to schedule the optimal one at inference time?
Virtuoso: Video-based Intelligence for real-time tuning on SOCs
First, the system does not consider energy consumption of the models while making a decision on which model to run.
SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation
The repeated cross-correlation and semi-FPN are designed based on this idea.
Temporal Early Exits for Efficient Video Object Detection
In this paper, we propose temporal early exits to reduce the computational complexity of per-frame video object detection.
SGE net: Video object detection with squeezed GRU and information entropy map
Compared with object detection of static images, video object detection is more challenging due to the motion of objects, while providing rich temporal information.
