2 code implementations • 26 Apr 2024 • Wei Cui, Rasa Hosseinzadeh, Junwei Ma, Tongzi Wu, Yi Sui, Keyvan Golestan
Contrastive learning is a model pre-training technique by first creating similar views of the original data, and then encouraging the data and its corresponding views to be close in the embedding space.
no code implementations • 10 Feb 2024 • Junwei Ma, Valentin Thomas, Guangwei Yu, Anthony Caterini
Foundation models have revolutionized tasks in computer vision and natural language processing.
no code implementations • 20 Sep 2022 • Junwei Ma, Bo Li, Qingchun Li, Chao Fan, Ali Mostafavi
To this end, this study creates a network embedding model capturing cross-county visitation networks, as well as heterogeneous features to uncover clusters of counties in the United States based on their pandemic spread transmission trajectories.
1 code implementation • CVPR 2022 • Satya Krishna Gorti, Noel Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guangwei Yu
Instead, texts often capture sub-regions of entire videos and are most semantically similar to certain frames within videos.
Ranked #17 on Video Retrieval on LSMDC (using extra training data)
1 code implementation • CVPR 2021 • Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Guangwei Yu
A common approach is to train a frame-level classifier where frames with the highest class probability are selected to make a video-level prediction.
Ranked #4 on Weakly Supervised Action Localization on FineAction
1 code implementation • NeurIPS 2019 • Chundi Liu, Guangwei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti
Despite recent progress in computer vision, image retrieval remains a challenging open problem.
no code implementations • 19 Nov 2019 • Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Ilya Stanevich, Guangwei Yu
We present a novel Cross-Class Relevance Learning approach for the task of temporal concept localization.
no code implementations • 12 Jun 2019 • Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guangwei Yu, Maksims Volkovs
We present our solution to Landmark Image Retrieval Challenge 2019.