18 citations · 35 across the 10 of their papers we have counts for
9 papers · 1 filter
FairNVT: Fair Classification via Noise Injection in Vision Transformers
Qiaoyue Tang, Sepidehsadat Hosseini, Mengyao Zhai +2
This paper presents FairNVT, a lightweight debiasing framework for pretrained transformer-based encoders that improves prediction fairness while preserving task performance. FairNV…
Ranking Regularization for Critical Rare Classes: Minimizing False Positives at a High True Positive Rate
Mohammadi Kiarash, Zhao He, Mengyao Zhai +1
In many real-world settings, the critical class is rare and a missed detection carries a disproportionately high cost. For example, tumors are rare and a false negative diagnosis c…
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
Mengyao Zhai, Lei Chen, Jiawei He +3
Humans accumulate knowledge in a lifelong fashion. Modern deep neural networks, on the other hand, are susceptible to catastrophic forgetting: when adapted to perform new tasks, th…
Adaptive Appearance Rendering
Mengyao Zhai, Ruizhi Deng, Jiacheng Chen +3
We propose an approach to generate images of people given a desired appearance and pose. Disentangled representations of pose and appearance are necessary to handle the compound va…
Generating Videos of Zero-Shot Compositions of Actions and Objects
Megha Nawhal, Mengyao Zhai, Andreas Lehrmann +2
Human activity videos involve rich, varied interactions between people and objects. In this paper we develop methods for generating such videos -- making progress toward addressing…
Lifelong GAN: Continual Learning for Conditional Image Generation
Mengyao Zhai, Lei Chen, Fred Tung +3
Lifelong learning is challenging for deep neural networks due to their susceptibility to catastrophic forgetting. Catastrophic forgetting occurs when a trained network is not able…
Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering
Mengyao Zhai, Jiacheng Chen, Ruizhi Deng +3
We propose an approach for forecasting video of complex human activity involving multiple people. Direct pixel-level prediction is too simple to handle the appearance variability i…
Deep Learning of Appearance Models for Online Object Tracking
Mengyao Zhai, Mehrsan Javan Roshtkhari, Greg Mori
This paper introduces a novel deep learning based approach for vision based single target tracking. We address this problem by proposing a network architecture which takes the inpu…
Deep Structured Models For Group Activity Recognition
Zhiwei Deng, Mengyao Zhai, Lei Chen +4
This paper presents a deep neural-network-based hierarchical graphical model for individual and group activity recognition in surveillance scenes. Deep networks are used to recogni…