Papers Action Localization
“Action Localization” 태그가 달린 논문 369편 · 필터 해제
PcmNet: Position-Sensitive Context Modeling Network for Temporal Action Localization
Temporal action localization is an important and challenging task that aims to locate temporal regions in real-world untrimmed videos where actions occur and recognize their classes. It is widely acknowledged that video …
Action LocalizationBoundary DetectionPositionTemporal Action Localization+2Modeling Multi-Label Action Dependencies for Temporal Action Localization
Real-world videos contain many complex actions with inherent relationships between action classes. In this work, we propose an attention-based architecture that models these action relationships for the task of temporal …
Action DetectionAction LocalizationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+1Single Run Action Detector over Video Stream -- A Privacy Preserving Approach
This paper takes initial strides at designing and evaluating a vision-based system for privacy ensured activity monitoring. The proposed technology utilizing Artificial Intelligence (AI)-empowered proactive systems offer…
Action LocalizationPrivacy PreservingActivity Graph Transformer for Temporal Action Localization
We introduce Activity Graph Transformer, an end-to-end learnable model for temporal action localization, that receives a video as input and directly predicts a set of action instances that appear in the video. Detecting …
Action LocalizationTemporal Action LocalizationPDAN: Pyramid Dilated Attention Network for Action Detection
Handling long and complex temporal information is an important challenge for action detection tasks. This challenge is further aggravated by densely distributed actions in untrimmed videos. Previous action detection meth…
Action DetectionAction LocalizationMulti-Label ClassificationTemporal Action LocalizationA Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization
Weakly supervised temporal action localization is a challenging vision task due to the absence of ground-truth temporal locations of actions in the training videos. With only video-level supervision during training, most…
Action LocalizationHard AttentionMultiple Instance LearningTemporal Action Localization+1Cross-Attentional Audio-Visual Fusion for Weakly-Supervised Action Localization
Temporally localizing actions in videos is one of the key components for video understanding. Learning from weakly-labelled data is seen a potential solution towards avoiding expensive frame-level annotations. Different …
Action LocalizationVideo UnderstandingWeakly Supervised Action LocalizationDivide and Conquer for Single-Frame Temporal Action Localization
Single-frame temporal action localization (STAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance. Existing methods adopt the one-stage framework but couple the…
Action LocalizationTemporal Action LocalizationCAG-QIL: Context-Aware Actionness Grouping via Q Imitation Learning for Online Temporal Action Localization
Temporal action localization has been one of the most popular tasks in video understanding, due to the importance of detecting action instances in videos. However, not much progress has been made on extending it to w…
Action LocalizationImitation LearningTemporal Action LocalizationVideo UnderstandingWeakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN
3D Convolutional Neural Network (3D CNN) captures spatial and temporal information on 3D data such as video sequences. However, due to the convolution and pooling mechanism, the information loss seems unavoidable. To imp…
Action ClassificationAction LocalizationAction RecognitionClassification+3Multi-shot Temporal Event Localization: a Benchmark
Current developments in temporal event or action localization usually target actions captured by a single camera. However, extensive events or actions in the wild may be captured as a sequence of shots by multiple camera…
Action LocalizationTemporal Action LocalizationPoint-Level Temporal Action Localization: Bridging Fully-supervised Proposals to Weakly-supervised Losses
Point-Level temporal action localization (PTAL) aims to localize actions in untrimmed videos with only one timestamp annotation for each action instance. Existing methods adopt the frame-level prediction paradigm to lear…
Action LocalizationPredictionTemporal Action LocalizationWeakly Supervised Action LocalizationTowards Improving Spatiotemporal Action Recognition in Videos
Spatiotemporal action recognition deals with locating and classifying actions in videos. Motivated by the latest state-of-the-art real-time object detector You Only Watch Once (YOWO), we aim to modify its structure to in…
Action DetectionAction LocalizationAction RecognitionAction Recognition In VideosD2-Net: Weakly-Supervised Action Localization via Discriminative Embeddings and Denoised Activations
This work proposes a weakly-supervised temporal action localization framework, called D2-Net, which strives to temporally localize actions using video-level supervision. Our main contribution is the introduction of a nov…
Action LocalizationDenoisingTemporal Action LocalizationWeakly Supervised Action Localization+1VideoMix: Rethinking Data Augmentation for Video Classification
State-of-the-art video action classifiers often suffer from overfitting. They tend to be biased towards specific objects and scene cues, rather than the foreground action content, leading to sub-optimal generalization pe…
Action LocalizationAction RecognitionClassificationData Augmentation+3Video Self-Stitching Graph Network for Temporal Action Localization
Temporal action localization (TAL) in videos is a challenging task, especially due to the large variation in action temporal scales. Short actions usually occupy a major proportion in the datasets, but tend to have the l…
Action LocalizationTemporal Action LocalizationReal-time Spatio-temporal Action Localization via Learning Motion Representation
Abstract. Most state-of-the-art spatio-temporal (S-T) action localization methods explicitly use optical flow as auxiliary motion information. Although the combination of optical flow and RGB significantly improves the p…
Action ClassificationAction LocalizationKnowledge DistillationOptical Flow Estimation+2TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Due to the large memory footprint of untrimmed videos, current state-of-the-art video localization methods operate atop precomputed video clip features. These features are extracted from video encoders typically trained …
Action ClassificationAction LocalizationDense Video CaptioningTemporal Action Localization+3SALAD: Self-Assessment Learning for Action Detection
Literature on self-assessment in machine learning mainly focuses on the production of well-calibrated algorithms through consensus frameworks i.e. calibration is seen as a problem. Yet, we observe that learning to be pro…
Action DetectionAction LocalizationTwo-Stream Consensus Network for Weakly-Supervised Temporal Action Localization
Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and localize all action instances in an untrimmed video under only video-level supervision. However, without frame-level annotations, it is challeng…
Action LocalizationTemporal Action LocalizationVocal Bursts Valence PredictionWeakly Supervised Action Localization+1