15 Result(s)
within
Conference Paper
Wenhai Wang
English
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Chapter and Conference Paper
Static Semantics Reconstruction for Enhancing JavaScript-WebAssembly Multilingual Malware Detection
The emergence of WebAssembly allows attackers to hide the malicious functionalities of JavaScript malware in cross-language interoperations, termed JavaScript-WebAssembly multilingual malware (JWMM). However, ...
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Chapter and Conference Paper
Applying Rely-Guarantee Reasoning on Concurrent Memory Management and Mailbox in \(\mu \) C/OS-II: A Case Study
Real-time operating systems (RTOSs) such as \(\mu \) μ C/OS-II are critical components of ma...
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Chapter and Conference Paper
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
Recently, computer vision foundation models such as CLIP and ALI-GN, have shown impressive generalization capabilities on various downstream tasks. But their abilities to deal with the long-tailed data still r...
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Chapter and Conference Paper
BEVFormer: Learning Bird’s-Eye-View Representation from Multi-camera Images via Spatiotemporal Transformers
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, wh...
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Chapter and Conference Paper
Guided Refine-Head for Object Detection
In recent years, multi-stage detectors improve the accuracy of object detection to a new level. However, due to multiple stages, these methods typically fall short in the inference speed. To alleviate this pro...
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Chapter and Conference Paper
TK-Text: Multi-shaped Scene Text Detection via Instance Segmentation
Benefit from the development of deep neural networks, scene text detectors have progressed rapidly over the past few years and achieved outstanding performance on several standard benchmarks. However, most exi...
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Chapter and Conference Paper
Differentiable Hierarchical Graph Grou** for Multi-person Pose Estimation
Multi-person pose estimation is challenging because it localizes body keypoints for multiple persons simultaneously. Previous methods can be divided into two streams, i.e. top-down and bottom-up methods. The top-...
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Chapter and Conference Paper
Scene Text Image Super-Resolution in the Wild
Low-resolution text images are often seen in natural scenes such as documents captured by mobile phones. Recognizing low-resolution text images is challenging because they lose detailed content information, le...
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Chapter and Conference Paper
AE TextSpotter: Learning Visual and Linguistic Representation for Ambiguous Text Spotting
Scene text spotting aims to detect and recognize the entire word or sentence with multiple characters in natural images. It is still challenging because ambiguity often occurs when the spacing between characte...
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Chapter and Conference Paper
Segmenting Transparent Objects in the Wild
Transparent objects such as windows and bottles made by glass widely exist in the real world. Segmenting transparent objects is challenging because these objects have diverse appearance inherited from the imag...
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Chapter and Conference Paper
A Novel 3D Human Action Recognition Framework for Video Content Analysis
Understanding the meanings of human actions from 3D skeleton data embedded videos is a new challenge in content-oriented video analysis. In this paper, we propose to incorporate temporal patterns of joint posi...
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Chapter and Conference Paper
Cloud of Line Distribution for Arbitrary Text Detection in Scene/Video/License Plate Images
Detecting arbitrary oriented text in scene and license plate images is challenging due to multiple adverse factors caused by images of diversified applications. This paper proposes a novel idea of extracting C...
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Chapter and Conference Paper
Hand Pose Estimation with Attention-and-Sequence Network
Hand pose estimation from depth images is an essential topic in computer vision. Despite the recent advancements in this area promoted by Convolutional Neural Network, accurate hand pose estimation is still a ...
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Chapter and Conference Paper
Cloud of Line Distribution and Random Forest Based Text Detection from Natural/Video Scene Images
Text detection in natural and video scene images is still considered to be challenging due to unpredictable nature of scene texts. This paper presents a new method based on Cloud of Line Distribution (COLD) an...
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Chapter and Conference Paper
Visual Robotic Object Gras** Through Combining RGB-D Data and 3D Meshes
In this paper, we present a novel framework to drive automatic robotic grasp by matching camera captured RGB-D data with 3D meshes, on which prior knowledge for grasp is pre-defined for each object type. The p...
