Neural View Synthesis (NVS) poses a complex challenge in generating realistic 3D scenes from multi-view videos, especially in diverse real-world scenarios. The limitations of current state-of-the-art (SOTA) NVS techniques become apparent when faced with variations in lighting, reflections, transparency, and overall scene complexity. Recognizing these challenges, researchers have aimed to push the boundaries of NVS…

The challenge of creating adaptable and versatile visual assistants has become increasingly evident in the rapidly evolving Artificial Intelligence. Traditional models often grapple with fixed capabilities and need help to learn dynamically from diverse examples. The need for a more agile and responsive visual assistant capable of adapting to new environments and tasks seamlessly sets…

Distinguishing fine image boundaries, particularly in noisy or low-resolution scenarios, remains formidable. Traditional approaches, heavily reliant on human annotations and rasterized edge representations, often need more precision and adaptability to diverse image conditions. This has spurred the development of new methodologies capable of overcoming these limitations. A significant challenge in this domain is the robust…