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Found 7 papers, 1 papers with code
STEPs: Self-Supervised Key Step Extraction and Localization from Unlabeled Procedural Videos
We address the problem of extracting key steps from unlabeled procedural videos, motivated by the potential of Augmented Reality (AR) headsets to revolutionize job training and performance.
Self-supervised Learning with Local Contrastive Loss for Detection and Semantic Segmentation
We evaluate our SSL approach on two downstream tasks -- object detection and semantic segmentation, using COCO, PASCAL VOC, and CityScapes datasets.
Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition
The lack of large-scale real datasets with annotations makes transfer learning a necessity for video activity understanding.
Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos
To our knowledge, this is the first Zero-Shot event detection model that is built on top of distributional semantics and extends it in the following directions: (a) semantic embedding of multimodal information in videos (with focus on the visual modalities), (b) automatically determining relevance of concepts/attributes to a free text query, which could be useful for other applications, and (c) retrieving videos by free text event query (e. g., "changing a vehicle tire") based on their content.
Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries
We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric context of the scene.
Pedestrian Detection in Low-resolution Imagery by Learning Multi-scale Intrinsic Motion Structures (MIMS)
In this paper, we give a comparative evaluation of the proposed method and demonstrate that MIMS outperforms the state of the art approaches in identifying pedestrians from low resolution airborne videos.
Recognizing Activities via Bag of Words for Attribute Dynamics
A video sequence is decomposed into short-term segments, which are characterized by the dynamics of their attributes.
