Browsing: AI News
Text-to-image (T2I) models are pivotal for creating, editing, and interpreting images. Google’s latest model, Imagen 3, delivers high-resolution outputs of 1024 × 1024 pixels, with options…
Recent AI advancements have notably impacted various sectors, particularly in image recognition and photorealistic image generation, with significant medical imaging and autonomous driving applications. However, the…
Accurate segmentation of structures like cells and organelles is crucial for deriving meaningful biological insights from imaging data. However, as imaging technologies advance, images’ growing size,…
A new research addresses a critical issue in Multimodal Large Language Models (MLLMs): the phenomenon of object hallucination. Object hallucination occurs when these models generate descriptions…
Diffusion models have set new benchmarks for generating realistic, intricate images and videos. However, scaling these models to handle high-resolution outputs remains a formidable challenge. The…
Multimodal Language Models MLLMs architectures have evolved to enhance text-image interactions through various techniques. Models like Flamingo, IDEFICS, BLIP-2, and Qwen-VL use learnable queries, while LLaVA…
Visual Simultaneous Localization and Mapping (SLAM) is a critical technology in robotics and computer vision that allows real-time state estimation for various applications. SLAM has become…
A key goal in the development of AI is the creation of general-purpose assistants utilizing Large Multimodal Models (LMMs). Building AI systems that can work in…
RGB-D cameras have a difficult time accurately capturing the depth of transparent objects because of the optical effects of reflection and refraction. Because of this, the…
Multimodal generative models represent an exciting frontier in artificial intelligence, focusing on integrating visual and textual data to create systems capable of various tasks. These tasks…