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Found 16 papers, 5 papers with code
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
We present Dynamic-SUPERB Phase-2, an open and evolving benchmark for the comprehensive evaluation of instruction-based universal speech models.
GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers
We trained a BERT model for downstream genre classification and used it to assess the results obtained with the genre-CTRL model.
Source Separation-based Data Augmentation for Improved Joint Beat and Downbeat Tracking
Due to advances in deep learning, the performance of automatic beat and downbeat tracking in musical audio signals has seen great improvement in recent years.
Automatic Composition of Guitar Tabs by Transformers and Groove Modeling
Deep learning algorithms are increasingly developed for learning to compose music in the form of MIDI files.
Sound Audio and Speech Processing
Analogical Image Translation for Fog Generation
AIT achieves this zero-shot image translation capability by coupling a supervised training scheme in the synthetic domain, a cycle consistency strategy in the real domain, an adversarial training scheme between the two domains, and a novel network design.
Unconditional Audio Generation with Generative Adversarial Networks and Cycle Regularization
Audio examples, as well as the code for implementing our model, will be publicly available online upon paper publication.
Unbiased Mean Teacher for Cross-domain Object Detection
We reveal that there often exists a considerable model bias for the simple mean teacher (MT) model in cross-domain scenarios, and eliminate the model bias with several simple yet highly effective strategies.
Score and Lyrics-Free Singing Voice Generation
Generative models for singing voice have been mostly concerned with the task of ``singing voice synthesis,'' i. e., to produce singing voice waveforms given musical scores and text lyrics.
Domain Agnostic Feature Learning for Image and Video Based Face Anti-spoofing
Face anti-spoofing is a measure towards this direction for bio-metric user authentication, and in particular face recognition, that tries to prevent spoof attacks.
Enhanced generative adversarial network for 3D brain MRI super-resolution
Single image super-resolution (SISR) reconstruction for magnetic resonance imaging (MRI) has generated significant interest because of its potential to not only speed up imaging but to improve quantitative processing and analysis of available image data.
Dixit: Interactive Visual Storytelling via Term Manipulation
In this paper, we introduce Dixit, an interactive visual storytelling system that the user interacts with iteratively to compose a short story for a photo sequence.
DLOW: Domain Flow for Adaptation and Generalization
In this work, we present a domain flow generation(DLOW) model to bridge two different domains by generating a continuous sequence of intermediate domains flowing from one domain to the other.
The 2018 DAVIS Challenge on Video Object Segmentation
Motivated by the analysis of the results of the 2017 edition, the main track of the competition will be the same than in the previous edition (segmentation given the full mask of the objects in the first frame -- semi-supervised scenario).
Calcium Removal From Cardiac CT Images Using Deep Convolutional Neural Network
Coronary calcium causes beam hardening and blooming artifacts on cardiac computed tomography angiography (CTA) images, which lead to overestimation of lumen stenosis and reduction of diagnostic specificity.
Video Object Segmentation Without Temporal Information
Video Object Segmentation, and video processing in general, has been historically dominated by methods that rely on the temporal consistency and redundancy in consecutive video frames.
Ranked #47 on
Semi-Supervised Video Object Segmentation
on DAVIS 2016
Semantically-Guided Video Object Segmentation
This paper tackles the problem of semi-supervised video object segmentation, that is, segmenting an object in a sequence given its mask in the first frame.
