Generative AI has revolutionized video synthesis, producing high-quality content with minimal human intervention. Multimodal frameworks combine the strengths of generative […]
Category: Computer Vision
ByteDance Research Introduces 1.58-bit FLUX: A New AI Approach that Gets 99.5% of the Transformer Parameters Quantized to 1.58 bits
Vision Transformers (ViTs) have become a cornerstone in computer vision, offering strong performance and adaptability. However, their large size and […]
Collective Monte Carlo Tree Search (CoMCTS): A New Learning-to-Reason Method for Multimodal Large Language Models
In today’s world, Multimodal large language models (MLLMs) are advanced systems that process and understand multiple input forms, such as […]
Microsoft and Tsinghua University Researchers Introduce Distilled Decoding: A New Method for Accelerating Image Generation in Autoregressive Models without Quality Loss
Autoregressive (AR) models have changed the field of image generation, setting new benchmarks in producing high-quality visuals. These models break […]
CoordTok: A Scalable Video Tokenizer that Learns a Mapping from Co-ordinate-based Representations to the Corresponding Patches of Input Videos
Breaking down videos into smaller, meaningful parts for vision models remains challenging, particularly for long videos. Vision models rely on […]
Deep Learning and Vocal Fold Analysis: The Role of the GIRAFE Dataset
Semantic segmentation of the glottal area from high-speed videoendoscopic (HSV) sequences presents a critical challenge in laryngeal imaging. The field […]
Evaluation Agent: A Multi-Agent AI Framework for Efficient, Dynamic, Multi-Round Evaluation, While Offering Detailed, User-Tailored Analyses
Visual generative models have advanced significantly in terms of the ability to create high-quality images and videos. These developments, powered […]
NOVA: A Novel Video Autoregressive Model Without Vector Quantization
Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at […]
This AI Paper from Microsoft and Oxford Introduce Olympus: A Universal Task Router for Computer Vision Tasks
Computer vision models have made significant strides in solving individual tasks such as object detection, segmentation, and classification. Complex real-world […]
Meta AI Releases Apollo: A New Family of Video-LMMs Large Multimodal Models for Video Understanding
While multimodal models (LMMs) have advanced significantly for text and image tasks, video-based models remain underdeveloped. Videos are inherently complex, […]