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Found 16 papers, 9 papers with code
A Recurrent Transformer Network for Novel View Action Synthesis
The transformed action is integrated with the target appearance using the proposed recurrent transformer network, which provides a transformed appearance for each time-step in the action sequence.
Multi-view Action Recognition using Cross-view Video Prediction
We evaluate the effectiveness of the learned representation for multi-view video action recognition in a supervised approach.
Navigating Hallucinations for Reasoning of Unintentional Activities
In this work we present a novel task of understanding unintentional human activities in videos.
EZ-CLIP: Efficient Zeroshot Video Action Recognition
Recent advancements in large-scale pre-training of visual-language models on paired image-text data have demonstrated impressive generalization capabilities for zero-shot tasks.
LARNet: Latent Action Representation for Human Action Synthesis
We present LARNet, a novel end-to-end approach for generating human action videos.
Pose-guided Generative Adversarial Net for Novel View Action Synthesis
We focus on the problem of novel-view human action synthesis.
TinyAction Challenge: Recognizing Real-world Low-resolution Activities in Videos
While various approaches have been shown effective for recognition task in recent works, they often do not deal with videos of lower resolution where the action is happening in a tiny region.
Unsupervised Discriminative Embedding for Sub-Action Learning in Complex Activities
This paper proposes a novel approach for unsupervised sub-action learning in complex activities.
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In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning
The recent research in semi-supervised learning (SSL) is mostly dominated by consistency regularization based methods which achieve strong performance.
We don't Need Thousand Proposals$\colon$ Single Shot Actor-Action Detection in Videos
We propose SSA2D, a simple yet effective end-to-end deep network for actor-action detection in videos.
View-invariant action recognition
The research in view-invariant action recognition addresses this problem and focuses on recognizing human actions from unseen viewpoints.
TinyVIRAT: Low-resolution Video Action Recognition
In real-world surveillance environments, the actions in videos are captured at a wide range of resolutions.
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
In this work we propose a capsule-based approach for semi-supervised video object segmentation.
Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries
The existing works on actor-action localization are mainly focused on localization in a single frame instead of the full video.
Time-Aware and View-Aware Video Rendering for Unsupervised Representation Learning
We demonstrate the effectiveness of the proposed method in rendering view-aware as well as time-aware video clips on two different real-world datasets including UCF-101 and NTU-RGB+D.
VideoCapsuleNet: A Simplified Network for Action Detection
In this work, we present a more elegant solution for action detection based on the recently developed capsule network.
