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Found 19 papers, 13 papers with code
Pixel-Level BPE for Auto-Regressive Image Generation
Pixel-level autoregression with Transformer models (Image GPT or iGPT) is one of the recent approaches to image generation that has not received massive attention and elaboration due to quadratic complexity of attention as it imposes huge memory requirements and thus restricts the resolution of the generated images.
OmniFusion Technical Report
We propose an \textit{OmniFusion} model based on a pretrained LLM and adapters for visual modality.
Ranked #39 on
Visual Question Answering
on MM-Vet
MERA: A Comprehensive LLM Evaluation in Russian
To address these issues, we introduce an open Multimodal Evaluation of Russian-language Architectures (MERA), a new instruction benchmark for evaluating foundation models oriented towards the Russian language.
Kandinsky 3.0 Technical Report
We focus on the key components that, as we have identified as a result of a large number of experiments, had the most significant impact on improving the quality of our model compared to the others.
FusionFrames: Efficient Architectural Aspects for Text-to-Video Generation Pipeline
The first stage concerns keyframes synthesis to figure the storyline of a video, while the second one is devoted to interpolation frames generation to make movements of the scene and objects smooth.
The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
In this study, we present an investigation into the anisotropy dynamics and intrinsic dimension of embeddings in transformer architectures, focusing on the dichotomy between encoders and decoders.
Kandinsky: an Improved Text-to-Image Synthesis with Image Prior and Latent Diffusion
Text-to-image generation is a significant domain in modern computer vision and has achieved substantial improvements through the evolution of generative architectures.
Ranked #22 on
Text-to-Image Generation
on MS COCO
MineralImage5k: A benchmark for zero-shot raw mineral visual recognition and description
On the contrary, in a raw sample, the target mineral can appear in the form of thinly represented inclusions.
RusTitW: Russian Language Text Dataset for Visual Text in-the-Wild Recognition
In this paper, we present a large-scale human-labeled dataset for Russian text recognition in-the-wild.
Eco2AI: carbon emissions tracking of machine learning models as the first step towards sustainable AI
The size and complexity of deep neural networks continue to grow exponentially, significantly increasing energy consumption for training and inference by these models.
RuCLIP -- new models and experiments: a technical report
In the report we propose six new implementations of ruCLIP model trained on our 240M pairs.
Survey on Large Scale Neural Network Training
Modern Deep Neural Networks (DNNs) require significant memory to store weight, activations, and other intermediate tensors during training.
A new face swap method for image and video domains: a technical report
Deep fake technology became a hot field of research in the last few years.
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Every modern neural network model has quite a few pointwise nonlinearities in its architecture, and such operation induces additional memory costs which -- as we show -- can be significantly reduced by quantization of the gradients.
Handwritten text generation and strikethrough characters augmentation
We introduce two data augmentation techniques, which, used with a Resnet-BiLSTM-CTC network, significantly reduce Word Error Rate (WER) and Character Error Rate (CER) beyond best-reported results on handwriting text recognition (HTR) tasks.
Emojich -- zero-shot emoji generation using Russian language: a technical report
This technical report presents a text-to-image neural network "Emojich" that generates emojis using captions in Russian language as a condition.
Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture
Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language.
StackMix and Blot Augmentations for Handwritten Text Recognition
This paper proposes a handwritten text recognition(HTR) system that outperforms current state-of-the-artmethods.
Ranked #1 on
Handwritten Text Recognition
on IAM-D
Digital Peter: Dataset, Competition and Handwriting Recognition Methods
This paper presents a new dataset of Peter the Great's manuscripts and describes a segmentation procedure that converts initial images of documents into the lines.
