China

China continues to set the pace in open-source large-language-model innovation, especially for agentic architectures and deep reasoning. Here is a comprehensive, up-to-date guide to...

Machine learning has increased considerably in several areas due to its performance in recent years. Thanks to modern computers' computing capacity and graphics cards,...

Object detection is a powerful technique for identifying objects in images and videos. Thanks to deep learning and computer vision advances, it has come...

Federated learning provides a mechanism to unleash data to fuel new AI applications by training AI models without letting anyone see or access your...

Deep learning has significantly advanced face recognition models based on convolutional neural networks. These models have a high accuracy rate and are used in...

Photo-realistic novel view synthesis and high-fidelity surface reconstruction have been made possible by recent developments in implicit brain representations. Unfortunately, most of the approaches...

A key entry point into the digital world, which is more prevalent in modern life for socializing, shopping, gaming, and other activities, is a...

Posters have been widely utilized in numerous commercial and nonprofit contexts to promote and disseminate information as a type of media with artistic and...

Neural radiance fields (NeRF) are a potent representation of 3D scenes, making it possible that they may one day replace photos and movies as...

Several popular geometric computer vision systems rely on local feature matching to function, such as Simultaneous Localization and Mapping (SLAM) and Structure-from-Motion (SFM). Detector-based...

Instance segmentation, useful in applications like autonomous driving, robotic manipulation, picture editing, cell segmentation, etc., tries to extract the pixel-wise mask labels of the...

Text generation models or casual language models are used to produce text on par with human-written text. Such related tasks are commonly referred to...

Large-scale text-to-image models, looking at you Stable Diffusion, have dominated the machine learning space in recent months. They have shown extraordinary generation performance in...

Language models are extensively used in real-world applications, which brings exciting new opportunities. However, this also increases the stakes of AI research and introduces...

Deep neural network design is crucial in computer vision for many applications, such as image and object recognition and video analysis. AlexNet, GoogleNet, ResNet,...

Deep learning technology is increasingly changing how people produce, enjoy, and share art, from concept design to real-time entertainment. The universe is portrayed in...

Humans typically use co-speech gestures to express their thoughts in addition to spoken channels throughout the everyday conversation. These nonverbal cues improve speech comprehension...

Recently, we are seeing the huge impact of language-guided image editing based on deep learning techniques that allow non-expert people to generate outstanding artistic...

Generative AI models have come an extremely long way in the last few years. Their capability increased significantly with the advancement of diffusion models....

Due to its potential usage in several Virtual Reality and Augmented Reality applications, the subject is becoming increasingly important. When given a collection of...

Recommender systems have drawn more and more interest recently from both academia and business. Despite the enormous achievements, reproducibility has always been a serious...

Tencent Holdings and Alibaba own AI models that have successfully passed a benchmark test CLUE. These test results indicate that these AI models can...

Object detection is the technique used to identify and classify various items in an image. Different methods are commonly used for object detection to...

Deep Neural Networks (DNNs) have succeeded greatly in several fields, including advertising systems, computer vision, and natural language processing. Large models with lots of...

The Chinese technology conglomerate Alibaba Group's subsidiary, Alibaba Cloud, serves as its technology and intelligence backbone. Founded in 2009, Alibaba Cloud aims to offer...

The goal of relation extraction (RE), which is helpful for many knowledge-driven activities, is to determine the semantic relationships between two elements in a...

Over the past decade, a surge in the number of businesses powered by recommendation techniques has been observed. Delivering personalized content for each user...

Contrastive Language-Image Pretraining, or CLIP, is a training method that differs from standard technics used by the vision community. A large dataset of over...

A DeepMind AI system called AlphaFold predicts the three-dimensional structure of proteins based on their amino acid composition. Since they were made available to...

Large-scale text-conditioned image generation models have shown impressive results in recent years. They can generate realistic-looking images given a text prompt. These models are...

Nowadays, text-to-image synthesis is gaining a lot of popularity. A diffusion probabilistic model is a class of latent variable models that have arisen to...

The text-to-image generation has come a long way in recent years. Text-to-image generation models that use large-scale training data and model parameters can now...

Over the last few years, video surveillance systems have experienced significant technological and economic expansion. In this context, the person re-identification (Re-ID) emerged. Re-ID...

Existing generative models, such as GAN, VAE, and flow-based models, suffer from mode collapse and must rely on surrogate objectives to approximate maximum likelihood...

Vision-Language Pre-training (VLP) models have made significant progress on several cross-modal tasks, such as Visual Question Answering (VQA) and cross-modal retrieval, during the previous...

Recognizing human actions in videos is an essential task for many applications. From helping coaches with player analysis in their sports teams to improving...

Electronic design automation (EDA), often known as computer-aided design (CAD), is a class of software tools used to create electronic systems like integrated circuits...

The Generative Adversarial Network (GAN) is a deep neural network architecture that may learn from training data and produce new data that shares the...

The goal of blind face restoration is to recover high-quality images of human faces from their low-quality counterparts that have been degraded for an...

Semantic segmentation, which tries to give a semantic category to each pixel, has gotten a lot of interest in the last decade as one...

Imagine you draw a line in a particular video frame, and you want to preserve that line in the upcoming frames. That means you...

One of the core applications of AI in recent years is to generate photos that are more and more realistic. Starting from VAEs, the...

Simultaneous localization and mapping (SLAM) is a system that estimates sensor postures while concurrently reconstructing a 3D map of the surrounding environment using a...

In recent years, deep neural networks (DNNs) have proven their efficiency for computer vision applications, such as image classification and segmentation. The use of...

Single Object Tracking (Sot) With Lidar Points Has Many Applications In Robotics And Automatic Driving. For example, the autonomous pedestrian following robot should be...

Constructing a high-definition map of street view is extremely useful and necessary for autonomous driving. An HD map of street view comprises all pedestrians...

Automatic speech recognition (ASR) has surpassed all other forms of modern human-machine interaction thanks to the proliferation of high-tech Internet of Things (IoT) gadgets....

A team of researchers created a new AI system that can explain its decision-making procedures to users who aren't computer scientists. The system may...

One of the most well-known one-stage object detection techniques is YOLOX, which is often utilized in various fields, including automated driving and defect checking....

Making an advanced vehicle-safety model or researching it requires a highly accurate annotated dataset. The dataset also must contain certain events that are critical...

In recent years, the generation of images or videos from different types of inputs (text, visual, or multimodal) has gained increased popularity. In this...

Numerous vision applications heavily rely on video recognition, including autonomous driving, sports video analysis, and microvideo recommendation. A temporal video model is showcased in...

Sipeed TinyMaix is an open-source machine learning library designed for microcontrollers. According to findings, it is lightweight enough to be compatible with Microchip ATmega328...

What all things would you expect from your most advanced text assistant, whether you are writing an academic report or a business email? It...

In computer vision, determining the posture of 3D objects from a single RGB image is crucial. This field is frequently separated into several tasks,...

By fusing much low dynamic range (LDR) photographs with different exposures, multi-frame high dynamic range (HDR) imaging tries to provide images with a more...

Object localization, a fundamental computer vision task, is crucial to many computer vision-based applications. While supervised approaches use manual location labels to learn to...

Proteins play crucial roles for an organism and are involved in nearly all biological processes. Studying protein structures and functions can significantly advance the...

Among the many applications of Deep Learning in healthcare, segmentation is undoubtedly one of the most studied, given the broad range of possible advantages...

The goal of video instance segmentation is to simultaneously find, segment, and track all instances of an object in a video. Due to the...

Gradient boosting decision trees is a sophisticated machine learning technique frequently utilized in real-world applications such as electronic advertising, search ranking, time-series prediction, and...

A recent research article found a relationship between dopaminergic activity and the TD(temporal difference) learning algorithm, giving basic insights into how the brain links...

The ability to identify non-trivial patterns in data using computational methods has sparked the creation of sophisticated machine intelligence systems with a wide range...

In the computer vision field, self-supervised representation learning has been a challenging problem for a long time. Self-supervised representation learning aims to learn transferrable...

With the worldwide anti-terrorist measures being strengthened, it is becoming more vital to undertake security checks in public locations to discover concealed items on...

AI is going through a paradigm shift with the invention of models like BERT and GPT-3. These models benefit greatly from big data at...

Data augmentation is creating additional data points from current data to increase the dataset size artificially. It is used to improve the performance and...

Portrait stylization aims to transform a person's appearance into more creative visual styles (e.g., 3D-cartoon, anime, and hand-drawn) while maintaining personal identity. This research...

Object tracking is one of the core applications in the field of computer vision. It constructs pixel-level or instance-level connections amongst frames and produces...

Aircraft classification is a widely studied task. It is considered a fine-grained image classification (FGVC) since all images belong to the same class. Because...

In recent years, the extension of transformers in the computer vision field has slowly made vision transformers (ViT) the state-of-the-art model for many topics,...

Real-time object identification is a critical issue in computer vision since it is frequently required in computer vision systems, including multi-object tracking, autonomous driving,...

The top cause of death for women globally is breast cancer. Due to its adaptability, safety, and high sensitivity, ultrasonic imaging is currently the...

Breast cancer is the most common and deadliest cancer for women. It is therefore essential to detect it early to reduce the risk of...

Visual perception is more adaptable and practical when an image is viewed as a graph. In computer vision, several networks handle the input image...

Analyzing images from subordinate categories such as airplane models or bird species is fine-grained image classification's main goal (FGVC) goal. Due to the fine-grained...

According to an article published in Business Insider, China launched the world's first seaborne drone carrier capable of functioning on its own last week....

This Article is written as a summay by Marktechpost Research Staff based on the paper 'CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers'. All Credit...

This Article is written as a summay by Marktechpost Staff based on the paper 'A federated graph neural network framework for privacy-preserving personalization'. All...

This Article is written as a summay by Marktechpost Staff based on the research paper 'Vision GNN: An Image is Worth Graph of Nodes'....

In logic synthesis, pre-mapping, technology mapping, and post-mapping optimizations are used to find equivalent representations of large-scale integrated circuits. LS is a sequential decision-making...

Machine learning and deep learning have gained popularity in domains, like computer vision (CV) and natural language processing (NLP), which require analyzing large amounts...

This Article Is Based On The Research Paper 'Quantum Self-Attention Neural Networks for Text Classification'. All Credit For This Research Goes To The Researchers...

This Article Is Based On The Research Article 'PaddleOCR, an Easy-to-Use and Open-Source OCR System, Rolls out Major Upgrade With Improved Accuracy and New...

This Article Is Based On The Research Paper 'LOEN: Lensless opto-electronic neural network empowered machine vision'. All Credit For This Research Goes To The...

This Article Is Based On The Research Paper 'Quantifying spatial homogeneity of urban road networks via graph neural networks'. All Credit For This Research...

This Article Is Based On The Research Paper 'Few-Shot Head Swapping in the Wild'. All Credit For This Research Goes To The Researchers 👏👏👏 Please...

This Article Is Based On The Research Paper 'CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers'. All Credit For This Research Goes To...

This Article Is Based On The Research Paper 'HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling'. All Credit For This Research Goes...

This Article Is Based On The Alibaba Research on FederatedScope. All Credit For This Research Goes To The Researchers 👏👏👏 Please Don't Forget To Join...

This Article Is Based On The Research Paper 'Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis'. All Credit For This...

This Article Is Based On The Research Paper '2^1296 Exponentially Complex Quantum Many-Body Simulation via Scalable Deep Learning Method'. All Credit For This Research...

This Article Is Based On The Research Paper 'CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP'. All Credit For This Research Goes To...

This Article Is Based On The Research Paper 'PP-Matting: High-Accuracy Natural Image Matting'. All Credit For This Research Goes To The Researchers Of This...

This article summary is based on the research paper: 'Solving ImageNet: a Unified Scheme for Training any Backbone to Top Results' All credits for this...

This research summary is based on the paper 'PP-YOLOE: An evolved version of YOLO' Please don't forget to join our ML Subreddit Object detection is a...

This research summary is based on the paper 'Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing' Please don't forget to join our ML Subreddit Face...

This article is based on the research paper 'SS-SAM : Stochastic Scheduled Sharpness-Aware Minimization for Efficiently Training Deep Neural Networks' Deep Neural Networks (DNNs) have...

This article is based on the research paper 'FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours' DeepMind released AlphaFold 2 last year,...

PLMs (pre-trained language models) have excelled at a variety of natural language processing (NLP) tasks. Auto-encoding and auto-regressive PLMs are the most common classifications...