Local 3D Editing via 3D Distillation of CLIP Knowledge-Reference-Cited by-同舟云学术

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Local 3D Editing via 3D Distillation of CLIP Knowledge

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Hyung Junha¹,Hwang Sungwon¹,Kim Daejin²,Lee Hyunji¹,Choo Jaegul¹

Affiliation:

1. KAIST AI

2. Scatter Lab

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205047.pdf?arnumber=10205047

Reference54 articles.

1. Image Style Transfer Using Convolutional Neural Networks

2. StyleGAN-NADA

3. Generative adversarial nets;goodfellow;Proc the Advances in Neural Information Processing Systems (NeurIPS),2014

4. Local Deep Implicit Functions for 3D Shape

5. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DILF: Differentiable rendering-based multi-view Image–Language Fusion for zero-shot 3D shape understanding;Information Fusion;2024-02

2. Multimodal Image Synthesis and Editing: The Generative AI Era;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12

3. Reconstruction of Neural Radiance Fields With Vivid Scenes in the Metaverse;IEEE Transactions on Consumer Electronics;2023

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