Medical image segmentation involves identifying regions of interest in medical images. In
modern times, there is a great need to develop robust computer vision algorithms to perform …

Recent text-to-image generation methods provide a simple yet exciting conversion capability
between text and image domains. While these methods have incrementally improved the …

Current object detectors are limited in vocabulary size due to the small scale of detection
datasets. Image classifiers, on the other hand, reason about much larger vocabularies, as …

Scaling up the size of vision models has been the de facto standard to obtain more powerful
visual representations. In this work, we discuss the point beyond which larger vision models …

Photorealistic rendering and reposing of humans is important for enabling augmented reality
experiences. We propose a novel framework to reconstruct the human and the scene that …

We present a new method that views object detection as a direct set prediction problem. Our
approach streamlines the detection pipeline, effectively removing the need for many hand …

Existing image fusion approaches are committed to using a single deep network to solve
different image fusion problems, achieving promising performance in recent years. However …

The annual cost of vehicle insurance fraud is estimated to exceed 40 billion dollars. This is
an enormous amount considering the number of new vehicles insured yearly. In terms of …

To understand how people look, interact, or perform tasks, we need to quickly and
accurately capture their 3D body, face, and hands together from an RGB image. Most …

The existence of humans and the preservation of the natural ecological equilibrium depend
greatly on trees. The semantic segmentation of trees is very important. It is crucial to learn …