University Of Texas At Austin

Text-to-image diffusion models represent an intriguing field in artificial intelligence research. They aim to create lifelike images based on textual descriptions utilizing diffusion models. The process involves iteratively generating samples from a basic distribution, gradually transforming...
Advancements in Artificial Intelligence (AI) and Deep Learning have brought a great transformation in the way humans interact with computers. With the introduction of diffusion models, generative modeling has shown remarkable capabilities in various applications, including...

The University of Texas Austin Researchers Propose HM3D-ABO: A Photo-realistic Dataset for Object-Centric Multi-View 3D Reconstruction

Since the rise in popularity of AR/VR applications, researchers have been studying the process of reconstructing 3D objects. Researchers can create data-driven algorithms for...

Meta AI and the University of Texas at Austin Researchers Open-Source Three New ML Models for Audio-Visual Understanding of Human Speech and Sounds in...

Acoustics significantly influence how we perceive moments. As society transitions to mixed and virtual realities, ongoing research is being done to produce high-quality sound...

Researchers from U Texas and Apple Propose a Novel Transformer-Based Architecture for Global Multi-Object Tracking

This research summary article is based on the research paper 'Global Tracking Transformers'. Multi-object tracking aims to locate and track all objects in a video...

UT Austin Researchers Demonstrate a Deep Learning Technique That Achieves High-Quality Image Reconstructions Based on MRI Datasets

During a magnetic resonance imaging (MRI) scan, time seems to stand still for many individuals. Those who have experienced one understand the difficulty of...

Researchers at Meta and the University of Texas at Austin Propose ‘Detic’: A Method to Detect Twenty-Thousand Classes using Image-Level Supervision

The difficulty of object detection is divided into two parts: detecting the object (localization) and labeling it (classification). Traditional techniques rely on box labels...

Researchers From Facebook AI And The University Of Texas At Austin Introduce VisualVoice: A New Audio-Visual Speech Separation Approach

Despite being present in surroundings with contaminated and overlapping sounds, the human perceptual system moves massively on visual information to lessen the audio’s ambiguities...

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