The renowned proverb, Numbers do not lie, underscores the reliability an...
Textual geographic information is indispensable and heavily relied upon ...
The renowned proverb that "The pen is mightier than the sword" underscor...
Large language models (LLMs), such as ChatGPT, have emerged with astonis...
A comprehensive understanding of interested human-to-human interactions ...
Monocular depth estimation has been actively studied in fields such as r...
HAZOP is a safety paradigm undertaken to reveal hazards in industry, its...
Hazards can be exposed by HAZOP as text information, and studying their
...
The hazard and operability analysis (HAZOP) report contains precious
ind...
LiDAR semantic segmentation essential for advanced autonomous driving is...
Most instance segmentation models are not end-to-end trainable due to ei...
In the task of Chinese named entity recognition based on deep learning,
...
Named entity recognition based on deep learning (DNER) can effectively m...
Hazard and operability analysis (HAZOP) is a remarkable representative i...
Multiple imputation (MI) is the state-of-the-art approach for dealing wi...
Nowadays in the field of semantic SLAM, how to correctly use semantic
in...
Siamese network based trackers formulate the visual tracking task as a
s...
Compared with the progress made on human activity classification, much l...
By decomposing the visual tracking task into two subproblems as
classifi...
According to observations, different visual objects have different salie...
Local feature descriptors have been widely used in fine-grained visual o...
The process of aligning a pair of shapes is a fundamental operation in
c...
Contextual information provides important cues for disambiguating visual...
In this paper, we tackle the problem of RGB-D semantic segmentation of i...
Convolutional-deconvolution networks can be adopted to perform end-to-en...
Human 3D pose estimation from a single image is a challenging task with
...
In the last few years, deep learning has led to very good performance on...
We propose a novel approach to enhance the discriminability of Convoluti...
This paper proposes a novel Affine Subspace Representation (ASR) descrip...
We propose a novel hybrid loss for multiclass and structured prediction
...