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Found 9 papers, 3 papers with code
2D Neural Fields with Learned Discontinuities
Effective representation of 2D images is fundamental in digital image processing, where traditional methods like raster and vector graphics struggle with sharpness and textural complexity respectively.
A Closer Look at the Limitations of Instruction Tuning
Our findings reveal that responses generated solely from pre-trained knowledge consistently outperform responses by models that learn any form of new knowledge from IT on open-source datasets.
Audio-driven Neural Gesture Reenactment with Video Motion Graphs
We present a method that reenacts a high-quality video with gestures matching a target speech audio.
APES: Articulated Part Extraction from Sprite Sheets
Rigged puppets are one of the most prevalent representations to create 2D character animations.
Learning Stylized Character Expressions from Humans
We present DeepExpr, a novel expression transfer system from humans to multiple stylized characters via deep learning.
Real-Time Lip Sync for Live 2D Animation
The emergence of commercial tools for real-time performance-based 2D animation has enabled 2D characters to appear on live broadcasts and streaming platforms.
Designing Style Matching Conversational Agents
Advances in machine intelligence have enabled conversational interfaces that have the potential to radically change the way humans interact with machines.
A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities
Embodied avatars as virtual agents have many applications and provide benefits over disembodied agents, allowing non-verbal social and interactional cues to be leveraged, in a similar manner to how humans interact with each other.
A Facial Affect Analysis System for Autism Spectrum Disorder
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence.
