How can high-quality images be generated without relying on human annotations? This paper from MIT CSAIL and FAIR Meta has addressed the challenge of...
Over the past few years, there have been significant advancements in Machine Learning (ML), with numerous frameworks and libraries developed to simplify our tasks....
The team of researchers from Google developed a new fine-tuning strategy to address the challenge of generating correct answers using LLMs. The strategy, called...
Researchers from FNii CUHKSZ, SSE CUHKSZ introduce MVHumanNet, a vast dataset for multi-view human action sequences with extensive annotations, including human masks, camera parameters,...
A team of researchers from the University of Wisconsin-Madison, NVIDIA, the University of Michigan, and Stanford University have developed a new vision-language model (VLM)...
Deep learning is finding its utility in all aspects of life. Its applications span diverse fields, from image and speech recognition to medical diagnosis...
How can the effectiveness of vision transformers be leveraged in diffusion-based generative learning? This paper from NVIDIA introduces a novel model called Diffusion Vision...
New text-to-image models have made tremendous strides recently, opening the door to revolutionary applications like picture creation from a single text input; in contrast...
Neural Radiance Fields (NeRF) represent an innovative 3D scene depiction technique in computer graphics and computer vision. Leveraging neural networks, this method is a...
With an increase in the use of the internet, the demand for high-quality and real-time video content and seamless experiences in applications like video...
In a groundbreaking development, researchers from ETH Zürich and the Max Planck Institute for Intelligent Systems have introduced HOLD, an innovative method designed to...
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