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Found 8 papers, 3 papers with code
Interpretable Machine Learning for Weather and Climate Prediction: A Survey
Advanced machine learning models have recently achieved high predictive accuracy for weather and climate prediction.
CNS-Edit: 3D Shape Editing via Coupled Neural Shape Optimization
First, we design the coupled neural shape (CNS) representation for supporting 3D shape editing.
EXIM: A Hybrid Explicit-Implicit Representation for Text-Guided 3D Shape Generation
This paper presents a new text-guided technique for generating 3D shapes.
CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape Exploration
This paper presents CLIPXPlore, a new framework that leverages a vision-language model to guide the exploration of the 3D shape space.
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
Finally, we demonstrate the scalability of SlotDiffusion to unconstrained real-world datasets such as PASCAL VOC and COCO, when integrated with self-supervised pre-trained image encoders.
Neural Wavelet-domain Diffusion for 3D Shape Generation, Inversion, and Manipulation
This paper presents a new approach for 3D shape generation, inversion, and manipulation, through a direct generative modeling on a continuous implicit representation in wavelet domain.
Neural Wavelet-domain Diffusion for 3D Shape Generation
This paper presents a new approach for 3D shape generation, enabling direct generative modeling on a continuous implicit representation in wavelet domain.
Neural Template: Topology-aware Reconstruction and Disentangled Generation of 3D Meshes
This paper introduces a novel framework called DTNet for 3D mesh reconstruction and generation via Disentangled Topology.
