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VisualRNet: Lightweight Camera Rotation Estimation from Low-Resolution Optical Flow via Cross-Modal Supervision. [PDF]

Sensors (Basel)
Yang X, Wang H, Ni J.
europepmc   +1 more source

Topic: "Color Image Processing: Models and Methods (CIP: MM)". [PDF]

Entropy (Basel)
Ramella G, Torcicollo I.
europepmc   +1 more source

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The Modality of Reconstruction in ‘Immodithymia’

Psychopathology, 2010
We studied the modality of reconstruction in the depressive patients whose premorbid personality presents ‘immodithymia’. The patients try to pursue the reconstruction limitlessly in obsessive ways. That is, there is no discharge from their reconstruction, and the limitless succession of reconstruction supports the patients’ existence. The hindrance of
M, Nakaya, K, Ohmori
openaire   +2 more sources

Collective Reconstructive Embeddings for Cross-Modal Hashing

IEEE Transactions on Image Processing, 2019
In this paper, we study the problem of cross-modal retrieval by hashing-based approximate nearest neighbor (ANN) search techniques. Most existing cross-modal hashing work mainly addresses the issue of multi-modal integration complexity using the same mapping and similarity calculation for data from different media types.
Mengqiu Hu, Yang Yang 0002, Fumin Shen, Ning Xie 0003, Richang Hong, Heng Tao Shen   +5 more
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Modal Reconstruction Methods With Zernike Polynomials

Journal of Refractive Surgery, 2005
ABSTRACT PURPOSE: To compare the advantages and disadvantages of different techniques for fitting Zernike polynomials to surfaces. METHODS: Two different methods, Orthogonal Projection and Gram-Schmidt orthogonalization, are compared in terms of speed and performance at fitting a complex object.
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Cross-Modal Representation Reconstruction for Zero-Shot Classification

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Zero-shot learning (ZSL) aims to recognize novel classes without training samples through transferring knowledge from seen classes, based on the assumption that both the seen and unseen classes share a latent semantic space. Previous works either focus on directly learning various mapping functions between visual space and semantic space, or searching ...
Yu Wang 0174, Shenjie Zhao
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Weakly Supervised Hashing with Reconstructive Cross-modal Attention

ACM Transactions on Multimedia Computing, Communications, and Applications, 2023
On many popular social websites, images are usually associated with some meta-data such as textual tags, which involve semantic information relevant to the image and can be used to supervise the representation learning for image retrieval. However, these user-provided tags are usually polluted by noise, therefore the main challenge lies in
Yongchao Du, Min Wang, Zhenbo Lu, Wengang Zhou, Houqiang Li   +4 more
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