[ad_1] Diffusion models are a significant component in generative models, particularly for image generation, and these models are undergoing transformative advancements. These models, functioning by transforming noise into structured data, especially images, through a denoising process, have become increasingly important in computer vision…

[ad_1] 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…

[ad_1] 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…

[ad_1] 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…

[ad_1] In the domain of computer vision, particularly in video-to-video (V2V) synthesis, maintaining temporal consistency across video frames has been a persistent challenge. Achieving this consistency is crucial for synthesized videos’ coherence and visual appeal, which often combine elements from varying sources or…

[ad_1] Raw and frequently unlabeled data can be retrieved and organized using representation learning. The ability of the model to develop a good representation depends on the quantity, quality, and diversity of the data. In doing so, the model mirrors the data’s inherent…

[ad_1] A promising new development in artificial intelligence called MobileVLM, designed to maximize the potential of mobile devices, has emerged. This cutting-edge multimodal vision language model (MMVLM) represents a major advancement in incorporating AI into common technology since it is built to function…

[ad_1] Image restoration is a complex challenge that has garnered significant attention from researchers. Its primary objective is to create visually appealing and natural images while maintaining the perceptual quality of the degraded input. In cases where there is no information available concerning…

[ad_1] Neural graphics primitives (NGP) are promising in enabling the smooth integration of old and new assets across various applications. They represent images, shapes, volumetric and spatial-directional data, aiding in novel view synthesis (NeRFs), generative modeling, light caching, and various other applications. Notably…

[ad_1] Object segmentation across images and videos is a complex yet pivotal task. Traditionally, this field has witnessed a siloed progression, with different tasks such as referring image segmentation (RIS), few-shot image segmentation (FSS), referring video object segmentation (RVOS), and video object segmentation…