Observing the close relationship among panoptic, semantic and instance
s...
It is commonly believed that high internal resolution combined with expe...
We design an open-vocabulary image segmentation model to organize an ima...
We present a combined scaling method called BASIC that achieves 85.7
zer...
Despite the fast progress in training specialized models for various tas...
We focus on the problem of domain adaptation when the goal is shifting t...
Building instance segmentation models that are data-efficient and can ha...
Pre-training is a dominant paradigm in computer vision. For example,
sup...
Convolutional neural networks typically encode an input image into a ser...
Despite the blooming success of architecture search for vision tasks in
...
Data augmentation is a critical component of training deep learning mode...
Current state-of-the-art convolutional architectures for object detectio...
Artistic style transfer is the problem of synthesizing an image with con...
Deep neural networks often work well when they are over-parameterized an...
In this paper, we present a method which combines the flexibility of the...
The presence of occluders significantly impacts object recognition accur...