Manzano combines visual understanding and text-to-image generation, while significantly reducing performance or quality trade-offs.

The idea of using the Apple II home computer for digital photography purposes may seem somewhat daft considering that this is not a purpose that they were ever designed for, yet this is the goal that ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

Abstract: Image segmentation is crucial in many fields, but existing image segmentation models based on encoder-decoder networks are constrained by manual parameter tuning and the limited ...

In the current multi-modality support within vLLM, the vision encoder (e.g., Qwen_vl) and the language model decoder run within the same worker process. While this tightly coupled architecture is ...

I've been transcoding videos on handbrake using AV1 which I think is the latest encoder. AV1 on the Mac is often incredibly efficient. I'm talking 3gb -> 300mb efficient. Even tougher material with ...

PyTorch implementation and pretrained models for High resolution Canopy Height Prediction inference. For details, see the paper: Very high resolution canopy height maps from RGB imagery using ...

Diffusion Transformers have demonstrated outstanding performance in image generation tasks, surpassing traditional models, including GANs and autoregressive architectures. They operate by gradually ...

As AI systems grow increasingly multimodal, the role of visual perception models becomes more complex. Vision encoders are expected not only to recognize objects and scenes, but also to support tasks ...

Abstract: In unsupervised medical image registration, encoder-decoder architectures are widely used to predict dense, full-resolution displacement fields from paired images. Despite their popularity, ...