End-to-end temporal action detection with transformer
Temporal action detection (TAD) aims to determine the semantic label and the temporal
interval of every action instance in an untrimmed video. It is a fundamental and challenging …
interval of every action instance in an untrimmed video. It is a fundamental and challenging …
Learning Models in Crowd Analysis: A Review
Crowd detection and counting are important tasks in several applications of crowd analysis
including traffic management, public safety and event planning. Automatic crowd counting …
including traffic management, public safety and event planning. Automatic crowd counting …
Proposal-based multiple instance learning for weakly-supervised temporal action localization
Weakly-supervised temporal action localization aims to localize and recognize actions in
untrimmed videos with only video-level category labels during training. Without instance …
untrimmed videos with only video-level category labels during training. Without instance …
Foreground activation maps for weakly supervised object localization
Weakly supervised object localization (WSOL) aims to localize objects with only image-level
labels, which has better scalability and practicability than fully supervised methods in the …
labels, which has better scalability and practicability than fully supervised methods in the …
Task-aware part mining network for few-shot learning
Abstract Few-Shot Learning (FSL) aims at classifying samples into new unseen classes with
only a handful of labeled samples available. However, most of the existing methods are …
only a handful of labeled samples available. However, most of the existing methods are …
Spatial-temporal based multihead self-attention for remote sensing image change detection
The neural network-based remote sensing image change detection method faces a large
amount of imaging interference and severe class imbalance problems under high-resolution …
amount of imaging interference and severe class imbalance problems under high-resolution …
Temporal action localization in the deep learning era: A survey
The temporal action localization research aims to discover action instances from untrimmed
videos, representing a fundamental step in the field of intelligent video understanding. With …
videos, representing a fundamental step in the field of intelligent video understanding. With …
Compact representation and reliable classification learning for point-level weakly-supervised action localization
Point-level weakly-supervised temporal action localization (P-WSTAL) aims to localize
temporal extents of action instances and identify the corresponding categories with only a …
temporal extents of action instances and identify the corresponding categories with only a …
A novel deep learning framework for automatic recognition of thyroid gland and tissues of neck in ultrasound image
L Ma, G Tan, H Luo, Q Liao, S Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recognition of thyroid glands and tissues of the neck is vital for screening related diseases
in ultrasound videos. This task is subjective, challenging, and dependent on the experience …
in ultrasound videos. This task is subjective, challenging, and dependent on the experience …
Imposing semantic consistency of local descriptors for few-shot learning
Few-shot learning suffers from the scarcity of labeled training data. Regarding local
descriptors of an image as representations for the image could greatly augment existing …
descriptors of an image as representations for the image could greatly augment existing …