1 citations · 1 across the 2 of their papers we have counts for
4 papers
VI3NR: Variance Informed Initialization for Implicit Neural Representations
Chamin Hewa Koneputugodage, Yizhak Ben-Shabat, Sameera Ramasinghe +1
Implicit Neural Representations (INRs) are a versatile and powerful tool for encoding various forms of data, including images, videos, sound, and 3D shapes. A critical factor in th…
GEOPARD: Geometric Pretraining for Articulation Prediction in 3D Shapes
Pradyumn Goyal, Dmitry Petrov, Sheldon Andrews +3
We present GEOPARD, a transformer-based architecture for predicting articulation from a single static snapshot of a 3D shape. The key idea of our method is a pretraining strategy t…
StyleMotif: Multi-Modal Motion Stylization using Style-Content Cross Fusion
Ziyu Guo, Young Yoon Lee, Joseph Liu +3
We present StyleMotif, a novel Stylized Motion Latent Diffusion model, generating motion conditioned on both content and style from multiple modalities. Unlike existing approaches…
Neural Experts: Mixture of Experts for Implicit Neural Representations
Yizhak Ben-Shabat, Chamin Hewa Koneputugodage, Sameera Ramasinghe +1
Implicit neural representations (INRs) have proven effective in various tasks including image, shape, audio, and video reconstruction. These INRs typically learn the implicit field…