11 citations · 35 across the 9 of their papers we have counts for
12 papers
A Full-duplex Speech Dialogue Scheme Based On Large Language Models
Peng Wang, Songshuo Lu, Yaohua Tang +3
We present a generative dialogue system capable of operating in a full-duplex manner, allowing for seamless interaction. It is based on a large language model (LLM) carefully align…
Towards Regression-Free Neural Networks for Diverse Compute Platforms
Rahul Duggal, Hao Zhou, Shuo Yang +3
With the shift towards on-device deep learning, ensuring a consistent behavior of an AI service across diverse compute platforms becomes tremendously important. Our work tackles th…
ELODI: Ensemble Logit Difference Inhibition for Positive-Congruent Training
Yue Zhao, Yantao Shen, Yuanjun Xiong +5
Negative flips are errors introduced in a classification system when a legacy model is updated. Existing methods to reduce the negative flip rate (NFR) either do so at the expense…
MeMOT: Multi-Object Tracking with Memory
Jiarui Cai, Mingze Xu, Wei Li +4
We propose an online tracking algorithm that performs the object detection and data association under a common framework, capable of linking objects after a long time span. This is…
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video Models
Feng Cheng, Mingze Xu, Yuanjun Xiong +4
We propose a memory efficient method, named Stochastic Backpropagation (SBP), for training deep neural networks on videos. It is based on the finding that gradients from incomplete…
Long Short-Term Transformer for Online Action Detection
Mingze Xu, Yuanjun Xiong, Hao Chen +4
We present Long Short-term TRansformer (LSTR), a temporal modeling algorithm for online action detection, which employs a long- and short-term memory mechanism to model prolonged s…
Harnessing Unrecognizable Faces for Improving Face Recognition
Siqi Deng, Yuanjun Xiong, Meng Wang +2
The common implementation of face recognition systems as a cascade of a detection stage and a recognition or verification stage can cause problems beyond failures of the detector.…
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
Yuanhan Zhang, Zhenfei Yin, Jing Shao +22
As facial interaction systems are prevalently deployed, security and reliability of these systems become a critical issue, with substantial research efforts devoted. Among them, fa…
DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
Liming Jiang, Zhengkui Guo, Wayne Wu +18
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection. The challenge employs the DeeperForensics-1.0 dataset, one of the…
Learning Self-Consistency for Deepfake Detection
Tianchen Zhao, Xiang Xu, Mingze Xu +3
We propose a new method to detect deepfake images using the cue of the source feature inconsistency within the forged images. It is based on the hypothesis that images' distinct so…
Positive-Congruent Training: Towards Regression-Free Model Updates
Sijie Yan, Yuanjun Xiong, Kaustav Kundu +5
Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error. In image classification, sample-wise i…
Towards causal benchmarking of bias in face analysis algorithms
Guha Balakrishnan, Yuanjun Xiong, Wei Xia +1
Measuring algorithmic bias is crucial both to assess algorithmic fairness, and to guide the improvement of algorithms. Current methods to measure algorithmic bias in computer visio…