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This research explores IEEE Transactions on Control Systems Technology, contributing new insights to the field of Artificial Intelligence.
Authors listed alphabetically We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of ob-jects. ShapeNet contains 3D models from a multitude of semant...
Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools. We demonstrate t...
A closed-form approximation of the exact unbiased inverse of the Anscombe variance-stabilizing transformation
This research explores IEEE Transactions on Neural Networks and Learning Systems, contributing new insights to the field of Artificial Intelligence.
This research explores IEEE Transactions on Systems, Man, and Cybernetics: Systems, contributing new insights to the field of Artificial Intelligence.
This research explores IEEE Transactions on Visualization and Computer Graphics, contributing new insights to the field of Artificial Intelligence.
In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. In view of this, the current article brin...
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. We are releasing the Segment Anything Model (SAM) and corresponding dataset (SA-1B) of 1B masks a...
We present ControlNet, a neural network architecture to add spatial conditioning controls to large, pretrained text-to-image diffusion models. We show that the training of ControlNets is robust with s...
Thematic analysis is a highly popular technique among qualitative researchers for analyzing qualitative data, which usually comprises thick descriptive data. By providing a methodological roadmap, thi...
We introduce LightGlue, a deep neural network that learns to match local features across images. This opens up exciting prospects for deploying deep matchers in latency-sensitive applications like 3D...
Recent research on remote sensing object detection has largely focused on improving the representation of oriented bounding boxes but has overlooked the unique prior knowledge presented in remote sens...
We introduce Zero-1-to-3, a framework for changing the camera viewpoint of an object given just a single RGB image. Our viewpoint-conditioned diffusion approach can further be used for the task of 3D...
When enhancing low-light images, many deep learning algorithms are based on the Retinex theory. The user study and application on low-light object detection also reveal the latent practical values of...
We propose a simple pairwise sigmoid loss for imagetext pre-training. Finally, we push the batch size to the extreme, up to one million, and find that the benefits of growing batch size quickly dimini...
Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation, and molecule design...
INTRODUCTION: Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve...
This research explores CLIP-Adapter: Better Vision-Language Models with Feature Ada..., contributing new insights to the field of Artificial Intelligence.