Summary of Wavelet Latent Diffusion (wala): Billion-parameter 3d Generative Model with Compact Wavelet Encodings, by Aditya Sanghi et al.
Wavelet Latent Diffusion (Wala): Billion-Parameter 3D Generative Model with Compact Wavelet Encodings
by Aditya Sanghi, Aliasghar Khani, Pradyumna Reddy, Arianna Rampini, Derek Cheung, Kamal Rahimi Malekshan, Kanika Madan, Hooman Shayani
First submitted to arxiv on: 12 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel approach called Wavelet Latent Diffusion (WaLa) that enables large-scale 3D generative models to efficiently capture fine details and complex geometries at high resolutions. The authors attribute the limitation of current representations to their inefficiency, which lacks compactness required for effective modeling. WaLa encodes 3D shapes into wavelet-based, compact latent encodings, achieving an impressive 2427x compression ratio with minimal loss of detail. This allows training large-scale generative networks without increasing inference time. The proposed models contain approximately one billion parameters and generate high-quality 3D shapes at 256^3 resolution. Additionally, WaLa offers rapid inference, producing shapes within two to four seconds depending on the condition. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary WaLa is a new way of creating 3D images that uses wavelet technology to make it more efficient. This means we can create much bigger and more detailed images without slowing down our computers. The authors tested their method on several datasets and found that it worked really well, producing high-quality images that are both diverse and accurate. They also made the code open-source so that others can use and build upon their work. |
Keywords
» Artificial intelligence » Diffusion » Inference
