7 citations · 14 across the 7 of their papers we have counts for
7 papers
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection
Xuhai Chen, Jiangning Zhang, Guanzhong Tian +5
This paper considers zero-shot Anomaly Detection (AD), performing AD without reference images of the test objects. We propose a framework called CLIP-AD to leverage the zero-shot c…
Multi-Agent Cooperation via Unsupervised Learning of Joint Intentions
Shanqi Liu, Weiwei Liu, Wenzhou Chen +2
The field of cooperative multi-agent reinforcement learning (MARL) has seen widespread use in addressing complex coordination tasks. While value decomposition methods in MARL have…
Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning
Jun Chen, Shipeng Bai, Tianxin Huang +3
Neural network quantization is a very promising solution in the field of model compression, but its resulting accuracy highly depends on a training/fine-tuning process and requires…
ViG-UNet: Vision Graph Neural Networks for Medical Image Segmentation
Juntao Jiang, Xiyu Chen, Guanzhong Tian +1
Deep neural networks have been widely used in medical image analysis and medical image segmentation is one of the most important tasks. U-shaped neural networks with encoder-decode…
MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection
Liang Liu, Boshen Zhang, Jiangning Zhang +6
Scale variation across object instances remains a key challenge in object detection task. Despite the remarkable progress made by modern detection models, this challenge is particu…
SelFSR: Self-Conditioned Face Super-Resolution in the Wild via Flow Field Degradation Network
Xianfang Zeng, Jiangning Zhang, Liang Liu +2
In spite of the success on benchmark datasets, most advanced face super-resolution models perform poorly in real scenarios since the remarkable domain gap between the real images a…
Audio2Face: Generating Speech/Face Animation from Single Audio with Attention-Based Bidirectional LSTM Networks
Guanzhong Tian, Yi Yuan, Yong liu
We propose an end to end deep learning approach for generating real-time facial animation from just audio. Specifically, our deep architecture employs deep bidirectional long short…