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Color ExtractionColor Extraction is a task in computer vision that involves the extraction and analysis of colors from images or videos. The objective of this task is to identify and isolate specific colors, or color ranges present in the visual data.
Background RemovalBackground Removal is an image processing technique, used to separate the main object from the background of a photo. Removing the background helps highlight the product, subject, or character, bringing a professional and aesthetically pleasing look to the image.
Image to AnimeThe goal of Image to Anime was to create a new version of the image that would possess the same clean lines and evoke the characteristic feel found in anime productions, capturing the unique artistry, and aesthetics associated with this style.
MediaPipe Face Mesh PlottingFace mesh detection, also known as facial landmark detection or face pose estimation, is the task of identifying and localizing specific keypoints or landmarks on a human face. It involves detecting the positions of facial features, such as eyes, eyebrows, nose, mouth, and jawline, in an image or video.
Video to Canny EdgeVideo to Canny Edge is the process of converting a video into a Canny edge representation, where edges in the video are emphasized and separated. Canny Edge is a popular algorithm in image processing and is often used to detect edges in images and videos.
MediaPipe Face DetectionFace detection is a computer vision technique that involves identifying and locating human faces within an image or video. The goal of face detection is to detect the presence of faces, and draw bounding boxes around them, without necessarily identifying specific facial features or landmarks.
Background ReplacementBackground Replacement is a powerful tool that enables users to easily change the background of their images, opening up endless possibilities for creative transformations, and visual enhancements.
Image Super-Resolution with SeemoReImage Super-Resolution with SeemoRe is a task aimed at improving the process of image super-resolution by leveraging expertise in the field. This task involves incorporating techniques that identify and utilize expert knowledge or specialized information to enhance the efficiency and accuracy of image upscaling.
Text Generation with SmolLM-135MText Generation with SmolLM-135M involves utilizing a compact language model with 135 million parameters to automatically generate text. This model, although smaller in size, is proficient at producing coherent and structured textual content.
Semantic-Guided Low-Light Image EnhancementSemantic-Guided Low-Light Image Enhancement is a task that integrates semantic information into the process of enhancing the quality of images captured in low-light conditions. By incorporating semantic guidance, this task aims to improve the accuracy and effectiveness of enhancing low-light images by considering the context and content of the scene.
Trending collections
Image-to-TextThe Image-to-Text task is an important task in the field of natural language processing and computer vision. Its purpose is to convert information within an image into readable and understandable text.
Object DetectionThe Object Detection task is an important task in the fields of computer vision and artificial intelligence. Its main objective is to detect and determine the position of objects within images or videos.
Image to ImageImage-to-Image is an important task in the field of image processing, where we convert images from one format or data type to another.
Housing Prices ChallengeHouse price prediction based on related factors such as house area, number of bedrooms, etc.
Trending datasets
Housing Prices ChallengeDataset for Housing Prices Challenge
NIH Chest X-RayNIH Chest X-Ray is a large dataset containing chest X-ray images of patients collected by the National Institutes of Health (NIH) of the United States.
CommonGenBuilding machines with commonsense to compose realistically plausible sentences is challenging. CommonGen is a constrained text generation task, associated with a benchmark dataset, to explicitly test machines for the ability of generative commonsense reasoning. Given a set of common concepts; the task is to generate a coherent sentence describing an everyday sce- nario using these concepts.
X-CSRTo create these datasets, the authors automatically translated the original CSQA and CODAH datasets, originally available only in English, into 15 other languages.
TextVQATextVQA is a dataset to benchmark visual reasoning based on text in images. TextVQA requires models to read and reason about text in images to answer questions about them.
PLOD: An Abbreviation Detection DatasetThis is the repository for PLOD Dataset subset being used for CW in NLP module 2023-2024 at University of Surrey.