Search Results for author:
Found 9 papers, 6 papers with code
Exploring Missing Modality in Multimodal Egocentric Datasets
Multimodal video understanding is crucial for analyzing egocentric videos, where integrating multiple sensory signals significantly enhances action recognition and moment localization.
TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks
Extensive experiments show that using features trained with our novel pretraining strategy significantly improves the performance of recent state-of-the-art methods on three tasks: Temporal Action Localization, Action Proposal Generation, and Dense Video Captioning.
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
To the best of our knowledge, XDC is the first self-supervised learning method that outperforms large-scale fully-supervised pretraining for action recognition on the same architecture.
MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds
In fact, we show how Morton features can be used to significantly improve performance (+3% for 2 popular semantic segmentation algorithms) in the task of semantic segmentation of point clouds on the challenging and large-scale S3DIS dataset.
RefineLoc: Iterative Refinement for Weakly-Supervised Action Localization
RefineLoc shows competitive results with the state-of-the-art in weakly-supervised temporal localization.
Temporal Localization
Weakly Supervised Action Localization
+2
The ActivityNet Large-Scale Activity Recognition Challenge 2018 Summary
The guest tasks focused on complementary aspects of the activity recognition problem at large scale and involved three challenging and recently compiled datasets: the Kinetics-600 dataset from Google DeepMind, the AVA dataset from Berkeley and Google, and the Moments in Time dataset from MIT and IBM Research.
Diagnosing Error in Temporal Action Detectors
Despite the recent progress in video understanding and the continuous rate of improvement in temporal action localization throughout the years, it is still unclear how far (or close?)
ActivityNet Challenge 2017 Summary
The ActivityNet Large Scale Activity Recognition Challenge 2017 Summary: results and challenge participants papers.
Action Search: Spotting Actions in Videos and Its Application to Temporal Action Localization
To address this need, we propose the new problem of action spotting in video, which we define as finding a specific action in a video while observing a small portion of that video.
