Search Results for author:
Found 8 papers, 2 papers with code
Semantic Guidance Tuning for Text-To-Image Diffusion Models
Based on this observation, we devise a technique to steer the guidance direction towards any concept from which the model diverges.
Utilizing Task-Generic Motion Prior to Recover Full-Body Motion from Very Sparse Signals
This is based on the premise that the ultimate goal of pose reconstruction is to reconstruct the motion, which is a series of poses.
ClothCombo: Modeling Inter-Cloth Interaction for Draping Multi-Layered Clothes
We present ClothCombo, a pipeline to drape arbitrary combinations of clothes on 3D human models with varying body shapes and poses.
F-RDW: Redirected Walking with Forecasting Future Position
In order to serve better VR experiences to users, existing predictive methods of Redirected Walking (RDW) exploit future information to reduce the number of reset occurrences.
Flexible Networks for Learning Physical Dynamics of Deformable Objects
This precondition restrains the model from generalizing to real-world data, which is considered to be a sequence of unordered point sets.
Discovering Latent Representations of Relations for Interacting Systems
However, existing approaches are difficult to apply if the number of relations is unknown or if the relations are complex.
Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks
Cloth simulation requires a fast and stable method for interactively and realistically visualizing fabric materials using computer graphics.
Building Emotional Machines: Recognizing Image Emotions through Deep Neural Networks
In this paper, we focus on two high level features, the object and the background, and assume that the semantic information of images is a good cue for predicting emotion.
