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Found 9 papers, 4 papers with code
GUESS:GradUally Enriching SyntheSis for Text-Driven Human Motion Generation
The whole text-driven human motion synthesis problem is then divided into multiple abstraction levels and solved with a multi-stage generation framework with a cascaded latent diffusion model: an initial generator first generates the coarsest human motion guess from a given text description; then, a series of successive generators gradually enrich the motion details based on the textual description and the previous synthesized results.
Ranked #6 on
Motion Synthesis
on KIT Motion-Language
Towards Detailed Text-to-Motion Synthesis via Basic-to-Advanced Hierarchical Diffusion Model
Besides, we introduce a multi-denoiser framework for the advanced diffusion model to ease the learning of high-dimensional model and fully explore the generative potential of the diffusion model.
Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video
Therefore, directly learning a mapping function from speech to the entire head image is prone to ambiguity, particularly when using a short video for training.
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
In this work, we propose a one-shot 3D facial avatar reconstruction framework that only requires a single source image to reconstruct a high-fidelity 3D facial avatar.
EE-TTS: Emphatic Expressive TTS with Linguistic Information
EE-TTS contains an emphasis predictor that can identify appropriate emphasis positions from text and a conditioned acoustic model to synthesize expressive speech with emphasis and linguistic information.
ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling
The research fields of parametric face model and 3D face reconstruction have been extensively studied.
Ranked #1 on
Face Alignment
on FaceScape
Maximum Entropy Population-Based Training for Zero-Shot Human-AI Coordination
We study the problem of training a Reinforcement Learning (RL) agent that is collaborative with humans without using any human data.
Recurrent Attention Network on Memory for Aspect Sentiment Analysis
We propose a novel framework based on neural networks to identify the sentiment of opinion targets in a comment/review.
Aspect-Based Sentiment Analysis (ABSA)
Feature Engineering
+1
