Results of the ICDAR 2015 Robust Reading Competition are presented. StradVision achieved the first ranks in 4 out of the 7 newly added tasks, i.e., Task 1.4 (Born Digital End-to-End, Strong), Task 2.4 (Focused Text End-to-End, Weak), Task 4.1 (Incidental Text Localisation), and Task 4.4 (Incidenta..
StradVision joined the ICDAR 2015 Competition on Text Reading in the Wild. There were several teams registered for the competition, but StradVision was the only one that submitted valid results for the detection task. Please find the sample results and the technical report by the organizer.1..
4 June 2015 CogniVue offers the most comprehensive embedded vision solution in the market today. StradVision joined Cognivue’s APEX Partner Program.
26 May 2015 Myunchul Sung, Bongjin Jun, Hojin Cho, Prof. Daijin Kim, all from StradVision, will present (ORAL) their latest work on scene text detection algorithm at International Conference on Document Analysis and Recognition (ICDAR) 2015. The paper is available here.
1 May 2015 The Embedded Vision Alliance is a collaboration to enable rapid growth of practical computer vision features in a diversity of systems and associated software. StradVision became a Technical Member of the Alliance in May 2015
15 Apr 2015 ARM is the world's leading semiconductor IP company. StradVision became a member of ARM Connected Community program on Apr 2015.
2 Apr 2015StradVision submitted its scene text detection and recognition results for Challenge 1 thru 4. Results will be announced during the ICDAR conference this summer. We have a preview results for Task 1 (Rank 1) and Task 2 (Rank 3) in Challenge 1, and Task 1 (Rank 1) and Task 2 (Rank 1) in C..
2 Mar 2015StradVision will present its latest advances in embedded computer vision in MWC – Hall 8.0 Stand 8.0E36. Our product and technology portfolio includes embedded vision software such as scene text detection & recognition, pedestrian detection, head & shoulder detection implem..
2014-Dec-08 Woonhyun Nam, an algorithm engineer of StradVision, presented his latest work on pedestrian detection algorithm at NIPS 2014, one of the top conferences in machine learning. For more details, please find his paper here