In this paper, we propose a new paradigm, named Historical Object Predic...
In this paper, we provide the observation that too few queries assigned ...
Training a large-scale deep neural network in a large-scale dataset is
c...
Data cleaning, architecture, and loss function design are important fact...
We present a conceptually simple, flexible, and universal visual percept...
Learning robust feature representation from large-scale noisy faces stan...
It is a challenging task to learn discriminative representation from ima...
It is a challenging task to learn rich and multi-scale spatiotemporal
se...
Vision transformers (ViTs) have become the popular structures and
outper...
Learning group representation is a commonly concerned issue in tasks whe...
This technical report introduces our winning solution to the spatio-temp...
This article introduces the solutions of the two champion teams, `MMfrui...
The small receptive field and capacity of minimal neural networks limit ...
The “shared head for classification and localization” (sibling head),
fi...
In this technical report, we briefly introduce the solutions of our team...
Large scale face recognition is challenging especially when the computat...
Fully convolutional neural network (FCN) has been dominating the game of...
One of the major restrictions on the performance of video-based person r...