This paper presents MOAT, a family of neural networks that build on top ...
The rise of transformers in vision tasks not only advances network backb...
We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-base...
Panoptic image segmentation is the computer vision task of finding group...
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a
...
In this work, we present BasisNet which combines recent advancements in
...
This paper studies the problem of novel category discovery on single- an...
In this paper, we tackle video panoptic segmentation, a task that requir...
In this paper, we present ViP-DeepLab, a unified model attempting to tac...
We present MaX-DeepLab, the first end-to-end model for panoptic segmenta...
This paper is concerned with ranking many pre-trained deep neural networ...
Mutual gaze detection, i.e., predicting whether or not two people are lo...
Convolution exploits locality for efficiency at a cost of missing long r...
In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast
...
Standard Knowledge Distillation (KD) approaches distill the knowledge of...
We present Panoptic-DeepLab, a bottom-up and single-shot approach for
pa...
Multi-scale context module and single-stage encoder-decoder structure ar...
We present the next generation of MobileNets based on a combination of
c...
We present a single-shot, bottom-up approach for whole image parsing. Wh...
The design of neural network architectures is an important component for...
Spatial pyramid pooling module or encode-decoder structure are used in d...
This paper proposes a deep learning architecture based on Residual Netwo...
The goal of this paper is to perform 3D object detection in the context ...
We introduce the MovieQA dataset which aims to evaluate automatic story
...
We describe an approach for unsupervised learning of a generic, distribu...
Books are a rich source of both fine-grained information, how a characte...
In this paper, we propose an approach that exploits object segmentation ...