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Found 11 papers, 1 papers with code
TAR3D: Creating High-Quality 3D Assets via Next-Part Prediction
We present TAR3D, a novel framework that consists of a 3D-aware Vector Quantized-Variational AutoEncoder (VQ-VAE) and a Generative Pre-trained Transformer (GPT) to generate high-quality 3D assets.
ClotheDreamer: Text-Guided Garment Generation with 3D Gaussians
We propose a novel representation Disentangled Clothe Gaussian Splatting (DCGS) to enable separate optimization.
TexDreamer: Towards Zero-Shot High-Fidelity 3D Human Texture Generation
Texturing 3D humans with semantic UV maps remains a challenge due to the difficulty of acquiring reasonably unfolded UV.
Efficient Apple Maturity and Damage Assessment: A Lightweight Detection Model with GAN and Attention Mechanism
This study proposes a method based on lightweight convolutional neural networks (CNN) and generative adversarial networks (GAN) for apple ripeness and damage level detection tasks.
PromptTTS 2: Describing and Generating Voices with Text Prompt
TTS approaches based on the text prompt face two main challenges: 1) the one-to-many problem, where not all details about voice variability can be described in the text prompt, and 2) the limited availability of text prompt datasets, where vendors and large cost of data labeling are required to write text prompts for speech.
Exploring Stochastic Autoregressive Image Modeling for Visual Representation
By introducing stochastic prediction and the parallel encoder-decoder, SAIM significantly improve the performance of autoregressive image modeling.
Semi-supervised Training for Knowledge Base Graph Self-attention Networks on Link Prediction
The task of link prediction aims to solve the problem of incomplete knowledge caused by the difficulty of collecting facts from the real world.
Modeling the Social Influence of COVID-19 via Personalized Propagation with Deep Learning
The resulting algorithm combines the personalized propagation of a neural prediction model with the approximate personalized propagation of a neural prediction model from page rank analysis.
Internal Language Model Estimation based Language Model Fusion for Cross-Domain Code-Switching Speech Recognition
More importantly, we train an end-to-end (E2E) speech recognition model by means of merging two monolingual data sets and observe the efficacy of the proposed ILME-based LM fusion for CSSR.
Internal Language Model Estimation Through Explicit Context Vector Learning for Attention-based Encoder-decoder ASR
In this paper we propose two novel approaches to estimate the ILM based on Listen-Attend-Spell (LAS) framework.
Efficient Scene Text Detection with Textual Attention Tower
Scene text detection has received attention for years and achieved an impressive performance across various benchmarks.
