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Search · four archives
25 papers · ranked by Valyu relevance
Junpeng Jing, Mao Ye, Krystian Mikolajczyk
Stereo Matching Authors: ['Junpeng Jing' 'Mao Ye' 'Krystian Mikolajczyk'] > Abstract. Dynamic stereo matching is the task of estimating consistent disparities from stereo videos with dynamic objects. Recent learningbased methods prioritize optimal performance on a single stereo pair, resulting in temporal…
Pengfei Liu, Kun Li, Helen Meng
Emotion recognition is a challenging and actively-studied research area that plays a critical role in emotion-aware humancomputer interaction systems. In a multimodal setting, temporal alignment between different modalities has not been well investigated yet. This paper presents a new model named as Gated Bidirectional…
Mengshun Hu, Kui Jiang, Zhixiang Nie, Zheng Wang
Spatial-Temporal Video Super-Resolution (ST-VSR) technology generates high-quality videos with higher resolution and higher frame rates. Existing advanced methods accomplish ST-VSR tasks through the association of Spatial and Temporal video super-resolution (S-VSR and T-VSR). These methods require two alignments and…
Jinxia Yang, Bing Su, Wayne Xin Zhao, Ji-Rong Wen
Multimodal Pre-training Authors: ['Jinxia Yang' 'Bing Su' 'Wayne Xin Zhao' 'Ji-Rong Wen'] Medical vision-language pre-training methods mainly leverage the correspondence between paired medical images and radiological reports. Although multi-view spatial images and temporal sequences of image-report pairs are available…
Jingbei Li, Meng Yi, Zhiyong Wu, Helen Meng + 3 more
'Yuping Wang' 'Yuxuan Wang'] Although deep learning and end-to-end models have been widely used and shown their superiority in automatic speech recognition (ASR) and text-to-speech (TTS) synthesis, state-of-the-art forced alignment (FA) models are still based on hidden Markov model (HMM). HMM has limited view of…
Wisnu Aditya, Timothy K. Shih, Tipajin Thaipisutikul, Arda Satata Fitriajie + 5 more
'Arda Satata Fitriajie' 'Munkhjargal Gochoo' 'Fitri Utaminingrum' 'Chih-Yang Lin' 'Loris Nanni' 'Leon Rothkrantz'] Given video streams, we aim to correctly detect unsegmented signs related to continuous sign language recognition (CSLR). Despite the increase in proposed deep learning methods in this area, most of them…
Ran Armoni, Elhanan Borenstein
A major challenge in working with longitudinal data when studying some temporal process is the fact that differences in pace and dynamics might overshadow similarities between processes. In the case of longitudinal microbiome data, this may hinder efforts to characterize common temporal trends across individuals or to…
Jiajun Zhang, Long Zhou, Yang Zhao, Chengqing Zong
In sequence to sequence generation tasks (e.g. machine translation and abstractive summarization), inference is generally performed in a left-to-right manner to produce the result token by token. The neural approaches, such as LSTM and self-attention networks, are now able to make full use of all the predicted history…
Nelson Johansen, Gerald Quon
Single cell RNA sequencing (scRNA-seq) experiments are now routinely being conducted on similar sets of cell types under different conditions and species, in order to characterize how gene regulation and cell identity respond to different stimuli and biological factors. The goal of scRNA-seq alignment is to compare…
Pietro Cinaglia, Mario Cannataro, Alessandro Giuliani, Adam Lipowski
In network analysis, real-world systems may be represented via graph models, where nodes and edges represent the set of biological objects (e.g., genes, proteins, molecules) and their interactions, respectively. This representative knowledge-graph model may also consider the dynamics involved in the evolution of the…
Pierre Colombo, Chouchang Yang, Giovanna Varni, Chloé Clavel
Sequence-to-sequence neural networks have been widely used in language-based applications as they have flexible capabilities to learn various language models. However, when seeking for the optimal language response through trained neural networks, current existing approaches such as beam-search decoder strategies are…
Lea Duncker, Maneesh Sahani
We introduce a novel scalable approach to identifying common latent structure in neural population spike-trains, which allows for variability both in the trajectory and in the rate of progression of the underlying computation. Our approach is based on shared latent Gaussian processes (GPs) which are combined linearly…
Santiago Marco-Sola, Jordan M. Eizenga, Andrea Guarracino, Benedict Paten + 2 more
Pairwise sequence alignment remains a fundamental problem in computational biology and bioinformatics. Recent advances in genomics and sequencing technologies demand faster and scalable algorithms that can cope with the ever-increasing sequence lengths. Classical pairwise alignment algorithms based on dynamic…
Rongpei Gou, Jingyi Yang, Menghan Guo, Yingjun Chen + 1 more
Central nervous system (CNS) drugs have had a significant impact on human health, e.g., treating a wide range of neurodegenerative and psychiatric disorders. In recent years, deep learning-based generative models, particularly those for designing drugs from scratch, have shown great potential for accelerating drug…
Marlou Rasenberg, Asli Özyürek, Mark Dingemanse
When people are engaged in social interaction, they can repeat aspects of each other’s communicative behavior, such as words or gestures. This kind of behavioral alignment has been studied across a wide range of disciplines and has been accounted for by diverging theories. In this paper, we review various…
Luca Del Pero, Susanna Ricco, Rahul Sukthankar, Vittorio Ferrari
We propose an automatic system for organizing the content of a collection of unstructured videos of an articulated object class (e.g., tiger, horse). By exploiting the recurring motion patterns of the class across videos, our system: (1) identifies its characteristic behaviors, and (2) recovers pixel-to-pixel…
Thaddeus R. Cybulski, Edward S. Boyden, George M. Church, Keith E. J. Tyo + 2 more
'Keith E. J. Tyo' 'Konrad P. Kording' 'Sergei L. Kosakovsky Pond'] Using a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of…
Frantisek Forgac, Dasa Munkova, Michal Munk, Livia Kelebercova
Parallel texts represent a very valuable resource in many applications of natural language processing. The fundamental step in creating parallel corpus is the alignment. Sentence alignment is the issue of finding correspondence between source sentences and their equivalent translations in the target text. A number of…
Christina Sartzetaki, Anne W. Zonneveld, Pablo Oyarzo, Alessandro T. Gifford + 3 more
The human brain is the most efficient and versatile system for processing dynamic visual input. By comparing representations from deep video models to brain activity, we can gain insights into mechanistic solutions for effective video processing, important to better understand the brain and to build better models.…
Mikko Rautiainen, Veli Mäkinen, Tobias Marschall
Graphs are commonly used to represent sets of sequences. Either edges or nodes can be labeled by sequences, so that each path in the graph spells a concatenated sequence. Examples include graphs to represent genome assemblies, such as string graphs and de Bruijn graphs, and graphs to represent a pan-genome and hence…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Mikko Rautiainen, Tobias Marschall
Graphs are commonly used to represent sets of sequences. Either edges or nodes can be labeled by sequences, so that each path in the graph spells a concatenated sequence. Examples include graphs to represent genome assemblies, such as string graphs and de Bruijn graphs, and graphs to represent a pan-genome and hence…
Yangwen Xu, Nicola Sartorato, Léo Dutriaux, Roberto Bottini
Humans conceptualize time in terms of space, allowing flexible time construals from various perspectives. We can travel internally through a timeline to remember the past and imagine the future (i.e., mental time travel) or watch from an external standpoint to have a panoramic view of history (i.e., mental time…
Authors not listed
A directed graph (or digraph) consists of a finite vertex set 𝑉 and a set of ordered edges 𝐸 ⊆ 𝑉 × 𝑉, each edge (𝑢, 𝑣) indicating a one-way connection from 𝑢 (source) to 𝑣 (target). A bidirected graph is a generalization of an undirected graph where each edge is assigned a direction at each of its endpoints…