[ad_1] The progress in neural rendering has brought significant breakthroughs in reconstructing scenes and generating new viewpoints. However, its effectiveness largely depends on the precise pre-computation of camera poses. To minimize this problem, many efforts have been made to train Neural Radiance Fields…

[ad_1] Object perception in images and videos unleashes the power of machines to decipher the visual world. Like virtual sleuths, computer vision systems scour pixels, recognizing, tracking, and understanding the myriad objects that paint the canvas of digital experiences. This technological prowess, fueled…

[ad_1] Video super-resolution, aiming to elevate the quality of low-quality videos to high fidelity, faces the daunting challenge of addressing diverse and intricate degradations commonly found in real-world scenarios. Unlike previous focuses on synthetic or specific camera-related degradations, the complexity arises from multiple…

[ad_1] 3D human motion reconstruction is a complex process that involves accurately capturing and modeling the movements of a human subject in three dimensions. This job becomes even more challenging when dealing with videos captured by a moving camera in real-world settings, as…

[ad_1] The field of pose estimation, which involves determining the position and orientation of an object in space, is a rapidly evolving area, with researchers continuously developing new methods to improve its accuracy and performance. Researchers from three highly regarded institutions – Tsinghua…

[ad_1] The Segment Anything Model (SAM) is an AI-powered model that segments images for object detection and recognition. It is an effective solution for various computer vision tasks. However, SAM is not optimized for edge devices, which can lead to retarded performance and…

[ad_1] Researchers from Carnegie Mellon University and Google DeepMind have collaborated to develop RoboTool, a system leveraging Large Language Models (LLMs) to imbue robots with the ability to creatively use tools in tasks involving implicit physical constraints and long-term planning. The system comprises…

[ad_1] Generative foundational models are a class of artificial intelligence models designed to generate new data that resembles a specific type of input data they were trained on. These models are often employed in various fields, including natural language processing, computer vision, music…

[ad_1] Many branches of biology, including ecology, evolutionary biology, and biodiversity, are increasingly turning to digital imagery and computer vision as research tools. Modern technology has greatly improved their capacity to analyze large amounts of images from museums, camera traps, and citizen science…