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3D-COCO is a dataset composed of MS COCO images with 3D models aligned on each instance. 3D-COCO was designed to achieve computer vision tasks such as 3D reconstruction or image detection configurable with textual, 2D image, and 3D CAD model queries.
3D-COCO is an extension of the original MS-COCO dataset providing 3D models and 2D-3D alignment annotations. We complete the existing MS-COCO dataset with 28K 3D models collected on ShapeNet and Objaverse. By using an IoU-based method, we match each MS-COCO annotation with the best 3D models to provide a 2D-3D alignment.
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476 Views
The dataset provides an end-to-end (E2E) perspective of the performance of 360-video services over mobile networks. The data was collected using a network-in-a-box setup in conjunction with a Meta Quest 2 head-mounted display (HMD) and a customer premises equipment (CPE) to provide 5G connectivity to the glasses (WiFi-native).
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143 Views
Dynamic malicious software detection aims to assess whether executable programs exhibit malicious behavior by thoroughly studying and analyzing their dynamic features. However, many current methodologies insufficiently explore the semantic features of API sequences and instead rely more on mining parameter information during API call processes to enhance detection performance. This leads to issues such as excessive dependence on prior knowledge, larger model parameter sizes, and higher computational complexities.
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294 Views
New capabilities involving sensors, data collection, and data analysis have enabled innovations in how engineered systems are monitored and maintained. Whereas each new evolution of maintenance philosophies has relied upon the current technological state, this research examines potential future capabilities in the field of prognostics and health management (PHM). PHM algorithms for predicting the estimated time to failure for a system are based on sensor data, physical models, or a combination of both.
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58 Views
Register allocation is an important phase in compiler optimization. Often, its resolution involves graph coloring, which is an NP-complete problem. Because of their significance, numerous heuristics have been suggested for their resolution. Heuristic development is a complex process that requires specialized domain expertise. Recently, several machine learning based approaches have been proposed to solve compiler optimization problems.
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153 Views
This study presents an automated approach for the generation of graphs from hand-drawn electrical circuit diagrams, aiming to streamline the digitization process and enhance the efficiency of traditional circuit design methods. Leveraging image processing, computer vision algorithms, and machine learning techniques, the system accurately identifies and extracts circuit components, capturing spatial relationships and diverse drawing styles.
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528 Views
This dataset contains a total of 6492 submissions, with 8% correct solutions and 87% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/scheduler-redux/ See the included PDF document for details about the original challenge.
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53 ViewsThis dataset contains a total of 18337 submissions, with 18% correct solutions and 55% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/caesar_redux/ See the included PDF document for details about the original challenge.
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31 ViewsThis dataset contains a total of 3271 submissions, with 14% correct solutions and 56% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/what-language-am-i-speaking/ See the included PDF document for details about the original challenge.
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7 ViewsThis dataset contains a total of 4461 submissions, with 6% correct solutions and 80% partial solutions. Link to the original challenge: https://csacademy.com/ieeextreme-practice/task/ordered-permutations/ See the included PDF document for details about the original challenge.
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8 Views