(Prof. Yong Man Ro, Sangmin Lee, Sungjune Park, from left)
Ph.D. Candidate Sangmin Lee and Sungjune Park (Prof. Yong Man Ro’s Lab) won the 1st place in the Ad-hoc Video Search (AVS) section of the 11th Video Browser Showdown (VBS 2022).
VBS is the international video retrieval competition held annually, and this year VBS 2022 is the 11th competition.
This year’s competition was held at Vietnam Phú Quốc for two days from June 6th to 7th, with 16 finalized video search teams from around the world.
The Ad-hoc Video Search section is to find as exact videos for given querys out of 2.5 million videos.
Sangmin Lee and Sungjune Park won the first place by constructing a multimodal search engine based on deep learning, which effectively searches target videos through the multi-modal correspondences of visual-audio-language latent representations.
The core algorithm adopted in the search engine, novel visual-audio representation learning method will be presented at CVPR 2022, the top tier conference in computer vision and AI field.
The title of the paper is “Weakly Paired Associative Learning for Sound and Image Representations via Bimodal Associative Memory”.
– Competition: 11th Video Browser Showdown 2022
– Award: Best AVS (1st place winner in Ad-hoc Video Search)
– Recipient: Sangmin Lee, Sungjune Park, Yong Man Ro (Advisory Professor)
