Multi-Stream Single Shot Spatial-Temporal Action Detection
We present a 3D Convolutional Neural Networks (CNNs) based single shot detector for spatial-temporal action detection tasks. Our model includes: (1) two short-term appearance and motion streams, with single RGB and optical flow image input separately, in order to capture the spatial and temporal information for the current frame; (2) two long-term 3D ConvNet based stream, working on sequences of continuous RGB and optical flow images to capture the context from past frames. Our model achieves strong performance for action detection in video and can be easily integrated into any current two-stream action detection methods. We report a frame-mAP of 71.30% on the challenging UCF101-24 actions dataset, achieving the state-of-the-art result of the one-stage methods. To the best of our knowledge, our work is the first system that combined 3D CNN and SSD in action detection tasks.
Code (0)
등록된 구현이 없습니다.
Tasks
Action DetectionOptical Flow EstimationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
CellStream: Dynamical Optimal Transport Informed Embeddings for Reconstructing Cellular Trajectories from Snapshots Data
Single-cell RNA sequencing (scRNA-seq), especially temporally resolved datasets, enables genome-wide profiling of gene expression dynamics at single-cell resolution across discrete time points. However, current technolog…
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks
In recent years, the deployment of large-scale pre-trained models in audio-visual downstream tasks has yielded remarkable outcomes. However, these models, primarily trained on single-modality unconstrained datasets, stil…
D3D: Distilled 3D Networks for Video Action Recognition
State-of-the-art methods for video action recognition commonly use an ensemble of two networks: the spatial stream, which takes RGB frames as input, and the temporal stream, which takes optical flow as input. In recent w…
Action ClassificationAction RecognitionOptical Flow EstimationTemporal Action LocalizationOne-Shot Action Recognition via Multi-Scale Spatial-Temporal Skeleton Matching
One-shot skeleton action recognition, which aims to learn a skeleton action recognition model with a single training sample, has attracted increasing interest due to the challenge of collecting and annotating large-scale…
Action RecognitionCustomize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models
Image customization has been extensively studied in text-to-image (T2I) diffusion models, leading to impressive outcomes and applications. With the emergence of text-to-video (T2V) diffusion models, its temporal counterp…
Video Generation