Computer Vision
This dataset is object tracking data for MOT challenge datasets.
The inferenced data is generated by Yolov5 and DeepSort.
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The problem of effective disposal of the trash generated by people has rightfully attracted major interest from various sections of society in recent times. Recently, deep learning solutions have been proposed to design automated mechanisms to segregate waste. However, most datasets used for this purpose are not adequate. In this paper, we introduce a new dataset, TrashBox, containing 17,785 images across seven different classes, including medical and e-waste classes which are not included in any other existing dataset.
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Guava fruit production is one of the main sources of economic growth in Asian countries, the world production of guava in 2019 was 55 million tons. Guava disease is an important factor in economic loss as well as quantity and quality of guava. The original guava fruit disease dataset consist of 38 images of phytophthora, 30 images of root and 34 images of scab guava disease with 650x650x3 pixel.
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Biometric management and that to which uses face, is indeed a very challenging work and requires a dedicated dataset which imbibes in it variations in pose, emotion and even occlusions. The Current work aims at delivering a dataset for training and testing purposes.SJB Face dataset is one such Indian face image dataset, which can be used to recognize faces. SJB Face dataset contains face images which were collected from digital camera. The face dataset collected has certain conditions such as different pose, Expressions, face partially occluded and with a uniform attire.
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Sign languages are the most common mode of communication with and between hearing-impaired individuals. In the Arab world, Arabic sign language is used with different dialects supporting a distinct set of rules for the gestures used. With research on natural language processing advancing, models have been developed to translate sign language to spoken language and vice versa. However, Arabic sign language has rarely been studied due to the lack of availability of datasets dealing with Arabic sign language.
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The dataset contains short video clips of four shoulder exercises.
- Arm flexion and extension
- Arm abduction and adduction
- Arm lateral and medial rotation
- Arm circumduction
The videos are labeled as either correct or incorrect.
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Deep video representation learning has recently attained state-of-the-art performance in video action recognition. However, when used with video clips from varied perspectives, the performance of these models degrades significantly. Existing VAR models frequently simultaneously contain both view information and action attributes, making it difficult to learn a view-invariant representation.
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Devanagari is a phonetic script that originated from Ancient Brahmi. It is the foundation of various Indian languages. According to data from the year 2022, the Devanagari Hindi script is spoken by over 342 million people worldwide and ranks third among the top 45 languages. There are approximately 11 vowels and 33 consonants and 10 numerals in the Devanagari script. The Devanagari script has no upper-or lower-case letters and is written from left to right.
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Not ready Yet
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Grasping and manipulating transparent objects with a robot is a challenge in robot vision. To successfully perform robotic grasping, 6D object pose estimation is needed. However, transparent objects are difficult to recognize because their appearance varies depending on the background, and modern 3D sensors cannot collect reliable depth data on transparent object surfaces due to the translucent, refractive, and specular surfaces. To address these challenges, we proposed a 6D pose estimation of transparent objects for manipulation.
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