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Your search keyword '"Luo, Jiebo"' showing total 29 results
Start Over Author "Luo, Jiebo" Journal ieee transactions on multimedia
29 results on '"Luo, Jiebo"'

17. Image Re-Attentionizing

Author

Nguyen, Tam V., primary, Ni, Bingbing, additional, Liu, Hairong, additional, Xia, Wei, additional, Luo, Jiebo, additional, Kankanhalli, Mohan, additional, and Yan, Shuicheng, additional

Published
2013
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28. Photo Stream Alignment and Summarization for Collaborative Photo Collection and Sharing.

Author

Yang, Jianchao, Luo, Jiebo, Yu, Jie, and Huang, Thomas S.

Abstract

With the popularity of digital cameras and camera phones, it is common for different people, who may or may not know each other, to attend the same event and take pictures and videos from different spatial or personal perspectives. Within the realm of social media, it is desirable to enable these people to select and share their pictures and videos in order to enrich memories and facilitate social networking. However, it is cumbersome to manually manage these photos from different cameras, of which the clocks settings are often not calibrated. In this paper, we propose automatic algorithms to address the above problems. First, we accurately align different photo streams or sequences from different photographers for the same event in chronological order on a common timeline, while respecting the time constraints within each photo stream. Given the preferred similarity measures (e.g., visual, and spatial similarities), our algorithm performs photo stream alignment via matching on a bipartite kernel sparse representation graph that forces the data connections to be sparse in an explicit fashion. Furthermore, we can produce a summary master stream from the aligned super stream of photos for efficient sharing by removing those redundant photos in the super stream while accounting for the temporal integrity. Based on a similar kernel sparse representation graph, our master stream summarization algorithm performs greedy backward selection to drop redundant photos without affecting the integrity of remaining photos for the entire event. We evaluate our algorithms on real-world personal online albums for 36 events and demonstrate its efficacy in automatically facilitating collaborative photo collection and sharing. [ABSTRACT FROM PUBLISHER]

Published
2012
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29. Cross Modality Bias in Visual Question Answering: A Causal View with Possible Worlds VQA.

Author

Vosoughi A, Deng S, Zhang S, Tian Y, Xu C, and Luo J

Abstract

To increase the generalization capability of VQA systems, many recent studies have tried to de-bias spurious language or vision associations that shortcut the question or image to the answer. Despite these efforts, the literature fails to address the confounding effect of vision and language simultaneously. As a result, when they reduce bias learned from one modality, they usually increase bias from the other. In this paper, we first model a confounding effect that causes language and vision bias simultaneously, then propose a counterfactual inference to remove the influence of this effect. The model trained in this strategy can concurrently and efficiently reduce vision and language bias. To the best of our knowledge, this is the first work to reduce biases resulting from confounding effects of vision and language in VQA, leveraging causal explain-away relations. We accompany our method with an explain-away strategy, pushing the accuracy of the questions with numerical answers results compared to existing methods that have been an open problem. The proposed method outperforms the state-of-the-art methods in VQA-CP v2 datasets. R2: Providing brief insights into the experimental setup and results would add valuable context for readers. In response to R2, we released the code and documentation for the implementation as follows. Our codes are available at https://github.com/ali-vosoughi/PW-VQA.

Published
2024
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