Papers Weakly Supervised Action Localization
“Weakly Supervised Action Localization” 태그가 달린 논문 55편 · 필터 해제
Weakly Supervised Action Selection Learning in Video
Localizing actions in video is a core task in computer vision. The weakly supervised temporal localization problem investigates whether this task can be adequately solved with only video-level labels, significantly reduc…
Temporal LocalizationWeakly Supervised Action LocalizationAction Unit Memory Network for Weakly Supervised Temporal Action Localization
Weakly supervised temporal action localization aims to detect and localize actions in untrimmed videos with only video-level labels during training. However, without frame-level annotations, it is challenging to achieve …
Action LocalizationDiversityTemporal Action LocalizationWeakly Supervised Action Localization+1ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization
Weakly-supervised temporal action localization aims to localize action instances temporal boundary and identify the corresponding action category with only video-level labels. Traditional methods mainly focus on foregrou…
Action LocalizationTemporal Action LocalizationWeakly Supervised Action LocalizationWeakly-supervised Temporal Action LocalizationAdaptive Mutual Supervision for Weakly-Supervised Temporal Action Localization
Weakly-supervised temporal action localization aims to localize actions in untrimmed videos with only video-level action category labels. Most of previous methods ignore the incompleteness issue of Class Activation Seque…
Action LocalizationTemporal Action LocalizationWeakly Supervised Action LocalizationWeakly-supervised Temporal Action LocalizationCoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning
Weakly-supervised temporal action localization (WS-TAL) aims to localize actions in untrimmed videos with only video-level labels. Most existing models follow the "localization by classification" procedure: locate tempor…
Action LocalizationCoLAContrastive LearningTemporal Action Localization+2ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
The object of Weakly-supervised Temporal Action Localization (WS-TAL) is to localize all action instances in an untrimmed video with only video-level supervision. Due to the lack of frame-level annotations during trainin…
Action LocalizationTemporal Action LocalizationVideo Polyp SegmentationWeakly Supervised Action Localization+1Temporal Action Segmentation from Timestamp Supervision
Temporal action segmentation approaches have been very successful recently. However, annotating videos with frame-wise labels to train such models is very expensive and time consuming. While weakly supervised methods tra…
Action SegmentationSegmentationTemporal Action SegmentationWeakly Supervised Action LocalizationCross-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 LocalizationWeakly-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+3Point-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 LocalizationD2-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+3Two-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+1Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization
Temporally localizing activities within untrimmed videos has been extensively studied in recent years. Despite recent advances, existing methods for weakly-supervised temporal activity localization struggle to recognize …
Metric LearningTripletWeakly Supervised Action LocalizationWeakly-supervised Temporal Action LocalizationRecognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
Recognition of surgical activity is an essential component to develop context-aware decision support for the operating room. In this work, we tackle the recognition of fine-grained activities, modeled as action triplets …
Action LocalizationAction RecognitionAction Triplet RecognitionTriplet+1Weakly-supervised Temporal Action Localization by Uncertainty Modeling
Weakly-supervised temporal action localization aims to learn detecting temporal intervals of action classes with only video-level labels. To this end, it is crucial to separate frames of action classes from the backgroun…
Action ClassificationAction LocalizationMultiple Instance LearningOut-of-Distribution Detection+3Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning
Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label. It can be solved under the Multiple Instance Learning (MIL) framework, whe…
Action LocalizationMultiple Instance LearningPseudo LabelWeakly Supervised Action LocalizationWeakly-Supervised Action Localization by Generative Attention Modeling
Weakly-supervised temporal action localization is a problem of learning an action localization model with only video-level action labeling available. The general framework largely relies on the classification activation,…
Action LocalizationTemporal Action LocalizationWeakly Supervised Action LocalizationWeakly-supervised Temporal Action LocalizationSF-Net: Single-Frame Supervision for Temporal Action Localization
In this paper, we study an intermediate form of supervision, i.e., single-frame supervision, for temporal action localization (TAL). To obtain the single-frame supervision, the annotators are asked to identify only a sin…
Action LocalizationTemporal Action LocalizationWeakly Supervised Action LocalizationAction Graphs: Weakly-supervised Action Localization with Graph Convolution Networks
We present a method for weakly-supervised action localization based on graph convolutions. In order to find and classify video time segments that correspond to relevant action classes, a system must be able to both ident…
Action LocalizationWeakly Supervised Action Localization