Papers › CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

19 Oct 2021arXiv:2110.09788archive 2025-07-28

Peng Zhou, Lingxi Xie, Bingbing Ni, Qi Tian

The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses. The recently proposed NeRF-based GANs made great progress towards 3D-aware generators, but they are unable to generate high-quality images yet. This paper presents CIPS-3D, a style-based, 3D-aware generator that is composed of a shallow NeRF network and a deep implicit neural representation (INR) network. The generator synthesizes each pixel value independently without any spatial convolution or upsampling operation. In addition, we diagnose the problem of mirror symmetry that implies a suboptimal solution and solve it by introducing an auxiliary discriminator. Trained on raw, single-view images, CIPS-3D sets new records for 3D-aware image synthesis with an impressive FID of 6.97 for images at the 256×256 resolution on FFHQ. We also demonstrate several interesting directions for CIPS-3D such as transfer learning and 3D-aware face stylization. The synthesis results are best viewed as videos, so we recommend the readers to check our github project at https://github.com/PeterouZh/CIPS-3D

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create_samples PeterouZh/CIPS-3D/piGAN_lib/extract_shapes.py official repository ran MIT (permissive) · 306b4b17e95e50e5 · report
get_current_step PeterouZh/CIPS-3D/piGAN_lib/curriculums.py official repository ran MIT (permissive) · a551faf28fc86a9f · report
last_upsample_step PeterouZh/CIPS-3D/piGAN_lib/curriculums.py official repository ran MIT (permissive) · 31312e8e88c4d95c · report
next_upsample_step PeterouZh/CIPS-3D/piGAN_lib/curriculums.py official repository ran MIT (permissive) · 738ade559b76771c · report
parser_args_from_list PeterouZh/CIPS-3D/bash/modelarts/start_modelarts_v2.py official repository ran MIT (permissive) · 24cae30ebed85892 · report
tensor_to_PIL PeterouZh/CIPS-3D/piGAN_lib/inverse_render.py official repository ran MIT (permissive) · ba5ab942e8001328 · report
generate_img PeterouZh/CIPS-3D/piGAN_lib/render_multiview_images.py official repository unverified MIT (permissive) · 397ffed73d1069ee · report
get_dataset PeterouZh/CIPS-3D/piGAN_lib/datasets.py official repository unverified MIT (permissive) · 5d4213f664c985e6 · report
get_dataset_distributed PeterouZh/CIPS-3D/piGAN_lib/datasets.py official repository unverified MIT (permissive) · 2172a94012703abe · report
sample_generator PeterouZh/CIPS-3D/piGAN_lib/extract_shapes.py official repository unverified MIT (permissive) · 3134951a7535b157 · report

Tasks

3D-Aware Image SynthesisImage GenerationNeRFTransfer Learning

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D-Aware Image Synthesis FFHQ 256 x 256 CIPS-3D FID 6.97 #1 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 CIPS-3D KID 2.87 #1 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 StyleNeRF FID 8.00 #2 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 StyleNeRF KID 3.70 #2 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 pi-GAN FID 34.56 #3 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 pi-GAN KID 26.58 #3 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 GIRAFFE FID 63.33 #4 of 4 Archive leaderboard report
3D-Aware Image Synthesis FFHQ 256 x 256 GIRAFFE KID 50.94 #4 of 4 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Convolution

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