602 citations · 2.6k across the 37 of their papers we have counts for
42 papers
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…
Contrastive Neighborhood Alignment
Pengkai Zhu, Zhaowei Cai, Yuanjun Xiong +4
We present Contrastive Neighborhood Alignment (CNA), a manifold learning approach to maintain the topology of learned features whereby data points that are mapped to nearby represe…
Learning Hierarchical Graph Neural Networks for Image Clustering
Yifan Xing, Tong He, Tianjun Xiao +6
We propose a hierarchical graph neural network (GNN) model that learns how to cluster a set of images into an unknown number of identities using a training set of images annotated…
Semi-TCL: Semi-Supervised Track Contrastive Representation Learning
Wei Li, Yuanjun Xiong, Shuo Yang +3
Online tracking of multiple objects in videos requires strong capacity of modeling and matching object appearances. Previous methods for learning appearance embedding mostly rely o…
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.…
Compatibility-aware Heterogeneous Visual Search
Rahul Duggal, Hao Zhou, Shuo Yang +4
We tackle the problem of visual search under resource constraints. Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery i…
Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates
Yuqing Xie, Yi-an Lai, Yuanjun Xiong +2
Behavior of deep neural networks can be inconsistent between different versions. Regressions during model update are a common cause of concern that often over-weigh the benefits in…
SSCAP: Self-supervised Co-occurrence Action Parsing for Unsupervised Temporal Action Segmentation
Zhe Wang, Hao Chen, Xinyu Li +4
Temporal action segmentation is a task to classify each frame in the video with an action label. However, it is quite expensive to annotate every frame in a large corpus of videos…
TubeR: Tubelet Transformer for Video Action Detection
Jiaojiao Zhao, Yanyi Zhang, Xinyu Li +10
We propose TubeR: a simple solution for spatio-temporal video action detection. Different from existing methods that depend on either an off-line actor detector or hand-designed ac…
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…
A Comprehensive Study of Deep Video Action Recognition
Yi Zhu, Xinyu Li, Chunhui Liu +7
Video action recognition is one of the representative tasks for video understanding. Over the last decade, we have witnessed great advancements in video action recognition thanks t…
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…
SMOT: Single-Shot Multi Object Tracking
Wei Li, Yuanjun Xiong, Shuo Yang +2
We present single-shot multi-object tracker (SMOT), a new tracking framework that converts any single-shot detector (SSD) model into an online multiple object tracker, which emphas…
Online Action Detection in Streaming Videos with Time Buffers
Bowen Zhang, Hao Chen, Meng Wang +1
We formulate the problem of online temporal action detection in live streaming videos, acknowledging one important property of live streaming videos that there is normally a broadc…
3D-Aided Data Augmentation for Robust Face Understanding
Yifan Xing, Yuanjun Xiong, Wei Xia
Data augmentation has been highly effective in narrowing the data gap and reducing the cost for human annotation, especially for tasks where ground truth labels are difficult and e…
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…
On Improving Temporal Consistency for Online Face Liveness Detection
Xiang Xu, Yuanjun Xiong, Wei Xia
In this paper, we focus on improving the online face liveness detection system to enhance the security of the downstream face recognition system. Most of the existing frame-based m…
Motion Guided 3D Pose Estimation from Videos
Jingbo Wang, Sijie Yan, Yuanjun Xiong +1
We propose a new loss function, called motion loss, for the problem of monocular 3D Human pose estimation from 2D pose. In computing motion loss, a simple yet effective representat…