Search Results for author:
Found 7 papers, 3 papers with code
Equivariance and Invariance Inductive Bias for Learning from Insufficient Data
We are interested in learning robust models from insufficient data, without the need for any externally pre-trained checkpoints.
Invariant Feature Regularization for Fair Face Recognition
Unfortunately, face datasets inevitably capture the imbalanced demographic attributes that are ubiquitous in real-world observations, and the model learns biased feature that generalizes poorly in the minority group.
Video-based Person Re-identification with Accumulative Motion Context
Video based person re-identification plays a central role in realistic security and video surveillance.
Neural Person Search Machines
We investigate the problem of person search in the wild in this work.
Ranked #4 on
Person Re-Identification
on CUHK-SYSU
Video-based Person Re-identification with Accumulative Motion Context
Video based person re-identification plays a central role in realistic security and video surveillance.
Towards Pose Invariant Face Recognition in the Wild
To this end, we propose a Pose Invariant Model (PIM) for face recognition in the wild, with three distinct novelties.
Conditional Convolutional Neural Network for Modality-Aware Face Recognition
Faces in the wild are usually captured with various poses, illuminations and occlusions, and thus inherently multimodally distributed in many tasks.
