Mining actionlet ensemble for action recognition with depth cameras
Human action recognition is an important yet challenging task. The recently developed
commodity depth sensors open up new possibilities of dealing with this problem but also …
commodity depth sensors open up new possibilities of dealing with this problem but also …
Deep learning technique for human parsing: A survey and outlook
Human parsing aims to partition humans in image or video into multiple pixel-level semantic
parts. In the last decade, it has gained significantly increased interest in the computer vision …
parts. In the last decade, it has gained significantly increased interest in the computer vision …
Articulated pose estimation by a graphical model with image dependent pairwise relations
We present a method for estimating articulated human pose from a single static image
based on a graphical model with novel pairwise relations that make adaptive use of local …
based on a graphical model with novel pairwise relations that make adaptive use of local …
Learning actionlet ensemble for 3D human action recognition
Human action recognition is an important yet challenging task. Human actions usually
involve human-object interactions, highly articulated motions, high intra-class variations, and …
involve human-object interactions, highly articulated motions, high intra-class variations, and …
Interpreting CNN knowledge via an explanatory graph
This paper learns a graphical model, namely an explanatory graph, which reveals the
knowledge hierarchy hidden inside a pre-trained CNN. Considering that each filter in a conv …
knowledge hierarchy hidden inside a pre-trained CNN. Considering that each filter in a conv …
From red wine to red tomato: Composition with context
Compositionality and contextuality are key building blocks of intelligence. They allow us to
compose known concepts to generate new and complex ones. However, traditional learning …
compose known concepts to generate new and complex ones. However, traditional learning …
Hierarchical human semantic parsing with comprehensive part-relation modeling
Modeling the human structure is central for human parsing that extracts pixel-wise semantic
information from images. We start with analyzing three types of inference processes over the …
information from images. We start with analyzing three types of inference processes over the …
Hierarchical human parsing with typed part-relation reasoning
Human parsing is for pixel-wise human semantic understanding. As human bodies are
underlying hierarchically structured, how to model human structures is the central theme in …
underlying hierarchically structured, how to model human structures is the central theme in …
Compositional convolutional neural networks: A robust and interpretable model for object recognition under occlusion
Computer vision systems in real-world applications need to be robust to partial occlusion
while also being explainable. In this work, we show that black-box deep convolutional …
while also being explainable. In this work, we show that black-box deep convolutional …
A survey on model based approaches for 2D and 3D visual human pose recovery
Human Pose Recovery has been studied in the field of Computer Vision for the last 40
years. Several approaches have been reported, and significant improvements have been …
years. Several approaches have been reported, and significant improvements have been …