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Found 28 papers, 9 papers with code
DeepRTE: Pre-trained Attention-based Neural Network for Radiative Tranfer
In this study, we propose a novel neural network approach, termed DeepRTE, to address the steady-state Radiative Transfer Equation (RTE).
Flow Matching based Sequential Recommender Model
Generative models, particularly diffusion model, have emerged as powerful tools for sequential recommendation.
RLCAD: Reinforcement Learning Training Gym for Revolution Involved CAD Command Sequence Generation
A CAD command sequence is a typical parametric design paradigm in 3D CAD systems where a model is constructed by overlaying 2D sketches with operations such as extrusion, revolution, and Boolean operations.
AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making
As agents progress, the environment adaptively generates new tasks with social structures for agents to undertake.
Efficient Sparse Attention needs Adaptive Token Release
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide array of text-centric tasks.
E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS
This paper introduces Embarrassingly Easy Text-to-Speech (E2 TTS), a fully non-autoregressive zero-shot text-to-speech system that offers human-level naturalness and state-of-the-art speaker similarity and intelligibility.
An Investigation of Noise Robustness for Flow-Matching-Based Zero-Shot TTS
Recently, zero-shot text-to-speech (TTS) systems, capable of synthesizing any speaker's voice from a short audio prompt, have made rapid advancements.
Total-Duration-Aware Duration Modeling for Text-to-Speech Systems
We also show that the proposed MaskGIT-based model can generate phoneme durations with higher quality and diversity compared to its regression or flow-matching counterparts.
Making Flow-Matching-Based Zero-Shot Text-to-Speech Laugh as You Like
In this work, we propose ELaTE, a zero-shot TTS that can generate natural laughing speech of any speaker based on a short audio prompt with precise control of laughter timing and expression.
NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription
The challenge focuses on distant speaker diarization and automatic speech recognition (DASR) in far-field meeting scenarios, with single-channel and known-geometry multi-channel tracks, and serves as a launch platform for two new datasets: First, a benchmarking dataset of 315 meetings, averaging 6 minutes each, capturing a broad spectrum of real-world acoustic conditions and conversational dynamics.
SpeechX: Neural Codec Language Model as a Versatile Speech Transformer
Recent advancements in generative speech models based on audio-text prompts have enabled remarkable innovations like high-quality zero-shot text-to-speech.
CTSN: Predicting Cloth Deformation for Skeleton-based Characters with a Two-stream Skinning Network
We present a novel learning method to predict the cloth deformation for skeleton-based characters with a two-stream network.
Real-Time Audio-Visual End-to-End Speech Enhancement
In this paper, we propose a low-latency real-time audio-visual end-to-end enhancement (AV-E3Net) model based on the recently proposed end-to-end enhancement network (E3Net).
StyleIPSB: Identity-Preserving Semantic Basis of StyleGAN for High Fidelity Face Swapping
StyleIPSB gives us a novel tool for high-fidelity face swapping, and we propose a three-stage framework for face swapping with StyleIPSB.
Exploring WavLM on Speech Enhancement
There is a surge in interest in self-supervised learning approaches for end-to-end speech encoding in recent years as they have achieved great success.
Real-Time Joint Personalized Speech Enhancement and Acoustic Echo Cancellation
Personalized speech enhancement (PSE) is a real-time SE approach utilizing a speaker embedding of a target person to remove background noise, reverberation, and interfering voices.
N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks
We present a novel mesh-based learning approach (N-Cloth) for plausible 3D cloth deformation prediction.
Sphere Face Model:A 3D Morphable Model with Hypersphere Manifold Latent Space
However, the shape parameters of traditional 3DMMs satisfy the multivariate Gaussian distribution while the identity embeddings satisfy the hypersphere distribution, and this conflict makes it challenging for face reconstruction models to preserve the faithfulness and the shape consistency simultaneously.
VarArray: Array-Geometry-Agnostic Continuous Speech Separation
Continuous speech separation using a microphone array was shown to be promising in dealing with the speech overlap problem in natural conversation transcription.
Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement
Performance analysis is also carried out by changing the ASR model, the data used for the ASR-step, and the schedule of the two update steps.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Reconstructing Recognizable 3D Face Shapes based on 3D Morphable Models
We compare our method with existing methods in terms of the reconstruction error, visual distinguishability, and face recognition accuracy of the shape parameters.
Multi-scale GCN-assisted two-stage network for joint segmentation of retinal layers and disc in peripapillary OCT images
An accurate and automated tissue segmentation algorithm for retinal optical coherence tomography (OCT) images is crucial for the diagnosis of glaucoma.
Hierarchical Optimization Time Integration for CFL-rate MPM Stepping
We propose Hierarchical Optimization Time Integration (HOT) for efficient implicit time-stepping of the Material Point Method (MPM) irrespective of simulated materials and conditions.
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Multispectral Pedestrian Detection via Simultaneous Detection and Segmentation
To narrow this gap, we propose a network fusion architecture, which consists of a multispectral proposal network to generate pedestrian proposals, and a subsequent multispectral classification network to distinguish pedestrian instances from hard negatives.
Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection
Multispectral images of color-thermal pairs have shown more effective than a single color channel for pedestrian detection, especially under challenging illumination conditions.
End-to-end detection-segmentation network with ROI convolution
We propose an end-to-end neural network that improves the segmentation accuracy of fully convolutional networks by incorporating a localization unit.
Segmentation-by-Detection: A Cascade Network for Volumetric Medical Image Segmentation
We propose an attention mechanism for 3D medical image segmentation.
A deep level set method for image segmentation
This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel.
