Generative Adversarial Networks (GANs) have been one of the main hypes of recent years. Based on the famous generator-discriminator mechanism, their very simple functioning...
Almost all of our computer interaction occurs via mouse, keyboards, and touch screens. An essential step in making human-computer interactions more efficient would be...
Visual tracking involves estimating the trajectory of an object in a video series, which is one of the fundamental challenges in computer vision. With...
Virtual try-on, virtual reality/augmented reality, and visual effects all use garment reconstruction. With the use of implicit representation or volumetric representation, extensive efforts have...
Images, such as graphics, paintings, and photographs, may frequently be explained in language, but they might also take specific talents and hours of effort...
In recent years, neural-based generative models have been at the center of attention for their exceptional capability of creating aesthetically attractive graphical content seemingly...
Federated Learning (FL) is a distributed learning paradigm that can learn a global or a personalized model for each user relying on decentralized data...
Machine learning provides researchers with excellent tools for identifying and predicting patterns and behavior. These tools are also capable of learning, optimizing, and performing...
Transformer models consistently obtain state-of-the-art computer vision tasks, including object detection and video classification. In standard convolutional approaches, images are processed pixel-by-pixel. To obtain...
The correspondence problem of visual alignment is one that computer vision algorithms must solve for many different applications.It's considered a critical element in Optical...
In machine learning pipelines, deep learning has proved successful in automating feature design. However, many researchers reveal that the techniques for improving neural network...
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