Have you ever come across an image or a video and noticed text within it, but couldn't quite make out what it said? Or have you ever seen signs or posters in public that were too far away to read clearly? These are common scenarios where text spotting can come in handy.
What is Text Spotting?
Text spotting refers to the ability to recognize and read text in natural scenes. It involves computer vision algorithms that analyze images or videos and extract text information in a way that is easily
Text-to-Image Generation is an exciting and emerging field of computer technology that combines computer vision and natural language processing. The goal of this task is to generate an image from a given text description by converting the input text into a meaningful representation, usually a feature vector. These feature vectors are then used to create an image that corresponds to the original text description.
How Does Text-to-Image Generation Work?
To understand text-to-image generation, o
Trajectory Prediction: Predicting the Spatial Coordinates of Road-Agents
Trajectory Prediction is a complex problem in the field of Artificial Intelligence that involves predicting the future spatial coordinates of various road-agents, such as cars, buses, pedestrians, and animals, based on their past and current behavior. This prediction can help autonomous vehicles avoid potential accidents and navigate more effectively.
Road-Agents and Their Dynamic Behavior
Road-agents are dynamic entiti
Unsupervised Anomaly Detection: Understanding the Basics
In today's technological landscape, large amounts of data are generated every second. This data is generally characterized into normal and abnormal data. Normal data is what is considered as the standard or regular data, while abnormal data are events or objects that are rare or outside the norm. Detecting anomalies in large data sets is very important because they can cause harm, lower the accuracy of models, and lead to data breaches. T
Unsupervised image-to-image translation is a technique used to convert an image into another image without any prior knowledge of pairings between the two. This task is performed without any ground truth image-to-image pairings, and the output image is completely new and unrelated to the input image.
The Basics of Unsupervised Image-to-Image Translation
To perform unsupervised image-to-image translation, a system uses a generative adversarial network (GAN) to train itself to map an input imag
Unsupervised Semantic Segmentation: An Overview
Unsupervised Semantic Segmentation is a technology that uses machine learning models to recognize the different objects in a picture or video frame and map them to their relevant class or category. This is done without seeing any pre-labeled ground truth classification of the objects, making it a powerful and flexible tool for image analysis in various fields of work.
How does Unsupervised Semantic Segmentation work?
Unsupervised Semantic Segme
Vehicle Speed Estimation
Vehicle speed estimation is a process to detect and monitor the speed of vehicles. This technology has grown any in recent years and is increasingly being used in many areas like traffic analysis, accident investigations, and surveillance. The system works by detecting and tracking vehicles as they pass through an area and then estimates their speed.
How does vehicle speed estimation work?
Vehicle speed estimation is based on traffic sensing technology that can detec
Overview of Video Frame Interpolation
Video Frame Interpolation is a technique used to synthesize new frames in between existing frames of a video. The purpose of this technique is to enhance video quality by creating additional smooth frames in a video, thereby improving its visual appeal. Video Frame Interpolation can also be used for creating slow-motion videos, increasing the video frame rate, and recovering lost frames in video streaming. This technique has several applications and is a vi
Video generation is a process of creating a new video sequence using machine learning algorithms. It uses existing videos, images or text inputs as the source material to generate new content that resembles the original data, and the generated result can be anything from Image to video or even Interactive Content. This emerging process is taking the internet by storm and has become increasingly popular in recent years with the advancements in Artificial Intelligence.
What is Video Generation?
What is Video Grounding?
Video grounding is a process of linking spoken words or natural language descriptions to corresponding video segments. A model is developed to achieve this goal which first receives a video and a description in natural language. The model then attempts to locate the precise video segment that aligns with the given description. This process could include determining the location of an object or action mentioned in the description within the video or identifying a specifi
Video object segmentation is a computer vision problem that involves separating objects in a video from their background. The goal is to identify which parts of an image or video clip contain an object and which do not. This task can be challenging because objects can move, change shape, or overlap with other objects. Solving it requires complex algorithms that analyze each frame of a video and distinguish between foreground and background regions.
Why is video object segmentation important?
Video prediction is an exciting field of study that involves predicting future frames in a video based on past video frames. This task may seem impossible at first, but with the advancements in machine learning and artificial intelligence, it has become more attainable.
What is Video Prediction?
The concept of video prediction involves using an algorithm to analyze patterns and movements in a video, and then using that information to predict the frames that will follow. This task involves a l
Video Question Answering (VideoQA) is a fascinating and rapidly growing field in the world of artificial intelligence. It is a technology that can answer natural language questions based on a given video. This means that when you watch a video, you can ask the VideoQA system questions about what you're watching, and it will give you accurate answers based on the content of the video.
What is Video Question Answering?
Video Question Answering (VideoQA) is a subfield of computer vision, which i
Overview of Video Retrieval
Video retrieval is a process that involves selecting a video that matches a text query. The video is selected from a pool of candidate videos, and the selection is based on document retrieval metrics. The objective of video retrieval is to find the video that corresponds to the text query and return it as a ranked list of candidates.
Video retrieval is used in a range of applications, including multimedia search engines, video surveillance systems, and personalized
What is Video Summarization?
Video summarization is a technique that aims to provide a shorter version of a video by selecting its most informative and important parts. It involves the process of analyzing the video content and extracting key-frames or key-fragments that can be used to create a summary of the video.
The main objective of video summarization is to provide users with a more concise and time-saving representation of a video, while still preserving its essential information. This
Video Super-Resolution is a computer vision technique used to increase the quality of low-resolution videos. It works by generating high-resolution video frames from low-resolution inputs. The end goal is to produce better-quality videos that are visually appealing to the viewer.
How Video Super-Resolution Works
The process of video super-resolution involves several steps. First, the low-resolution video is divided into smaller parts or patches, and these patches are analyzed to extract their
Video Understanding is a complex field that involves recognizing and localizing different actions or events that appear in a video. This process requires the use of advanced technologies that can analyze the visual and audio information contained in the video and identify patterns and features that correspond to specific actions or events.
What is Video Understanding?
Video Understanding is a subfield of Computer Vision that focuses on developing algorithms and techniques that enable computer
Introduction to Visual Dialog
Visual Dialog is a field of Artificial Intelligence that enables computers to have a meaningful conversation with humans about visual content. In simple terms, it involves answering questions about images through a natural and conversational language with an AI agent. The task involves providing an accurate response to a question, given an image, a dialog history, and a follow-up question about the image. The purpose behind Visual Dialog is to bridge the gap betwee
