In this post, we discuss what multimodals are, how they work, and their impact on solving computer vision problems.
The research progress in multimodal learning has grown rapidly over the last decade in several areas, especially in computer vision. The growing potential
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models; Lingxi Xie et al A Path Towards Autonomous Machine Intelligence; Yann LeCun et al GPT-4 Can’t Reason; Konstantine Arkoudas et al Cognitive Architectures for Language Agents; Theodore Sumers et al Large Search...
SALSA: A Multimodal Dataset for the Automated Analysis of Free-Standing Social InteractionsThe automated study of free interactions in unstructured social gatherings (e.g., cocktail party ) has attracted much attention from the computer science community, and is also of critical importance to other ...
Emotion analysis and recognition has become an interesting topic of research among the computer vision research community. In this paper, we first present the emoF-BVP database of multimodal (face, body gesture, voice and physiological signals) recordings of actors enacting various expressions of em...
Intuitively, feeding multiple modalities of data to vision transformers could improve the performance, yet the inner-modal attentive weights may also be diluted, which could thus undermine the final performance. In this paper, we propose a multimodal token fusion method (TokenFusion), tailored for ...
StyleSpace analysis: Disentangled controls for StyleGAN image generation. In Proc. the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun. 2021, pp.12858–12867. DOI: https://doi.org/10.1109/cvpr46437.2021.01267. Liu Z H, Feng R L, Zhu K, Zhang Y F, Zheng...
A federated learning system with data fusion for healthcare using multi-party computation and additive secret sharing T Muazu, Y Mao, AU Muhammad, M Ibrahim, UMM Kumshe, O Samuel Computer Communications, 202402 PUB Medical report generation based on multimodal federated learning J Chen, R Pan C...
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for UWB sensing7. FMCW radar is also an optional choice which has been proven in the result of the paper8. The mentioned work adopts point clouds of human mouth while speaking as data feature for classification work of 13 words with 4 speakers. It gains 88% accuracy using Linear Regression...