New Apple model combines vision understanding and image generation with impressive results

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

Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

T5Gemma 2 follows the same adaptation idea introduced in T5Gemma, initialize an encoder-decoder model from a decoder-only checkpoint, then adapt with UL2. In the above figure the research team show ...
IEEE

Multiresolution Encoder-Decoder Convolutional Neural Network for Magnetic Resonance Image Segmentation

Abstract: In image segmentation by deep learning, encoder-decoder Convolutional Neural Network (CNN) architectures are fundamental for creating and learning representations. However, with many filters ...
IEEE

GAN-Based Encoder-Decoder Method for Image Deblurring

Abstract: Image deblurring is one of the classic tasks in the field of computer vision, holding significant research importance and practical value. The Multi-Input Multi-Output (MIMO) encoder-decoder ...
Hackaday

Optimizing A QuickTake Image Decoder For The Apple II’s 6502

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 ...
GitHub

encoder-decoder

Store any user state in query parameters; imagine JSON in a browser URL, while keeping types and structure of data, e.g.numbers will be decoded as numbers not strings. With TS validation. Shared state ...
University of Dayton

Signal and Image Processing Lab

UD's Signal and Image Processing Lab is designed to support graduate and undergraduate research in the areas of signal and image processing. The lab provides office space for graduate students and has ...
Android Authority

Pixel users say Google's image processing is ruining shots. Are you affected?

Several Pixel users are reporting discrepancies between their camera viewfinder previews and the final processed photos. Most of the complaints focus on over-processed images with inaccurate color ...
marktechpost

Decoupled Diffusion Transformers: Accelerating High-Fidelity Image Generation via Semantic-Detail Separation and Encoder Sharing

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

A Combination Method of Stacked Convolutional Auto-Encoder and Selective Kernel Attention Mechanism for Image Classification ()

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
GitHub

Allow static cache to be larger than sequence length / batch size for encoder-decoder models

the cross-attention cache size must equal the encoder sequence length. batch size for both self-attention and cross-attention caches must be the same as the generating batch size. I have been working ...