For the last few decades, several major subfields of artificial intelligence including computer
vision, graphics, and robotics have progressed largely independently from each other …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

In this paper, we focus on designing effective method for fast and accurate scene parsing. A
common practice to improve the performance is to attain high resolution feature maps with …

Our objective is to transform a video into a set of discrete audio-visual objects using self-
supervised learning. To this end, we introduce a model that uses attention to localize and …

We notice information flow in convolutional neural networks is restricted inside local
neighborhood regions due to the physical design of convolutional filters, which limits the …

Differentiable image sampling in the form of backward warping has seen broad adoption in
tasks like depth estimation and optical flow prediction. In contrast, how to perform forward …

Scene parsing aims to assign a class (semantic) label for each pixel in an image. It is a
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …

Semantic segmentation requires large amounts of pixel-wise annotations to learn accurate
models. In this paper, we present a video prediction-based methodology to scale up training …

In this paper, we present a new large-scale dataset for the video panoptic segmentation
task, which aims to assign semantic classes and track identities to all pixels in a video. As …