High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimization

1 code implementation • CVPR 2023 • Jiaxin Xie, Hao Ouyang, Jingtan Piao, Chenyang Lei, Qifeng Chen

We present a high-fidelity 3D generative adversarial network (GAN) inversion framework that can synthesize photo-realistic novel views while preserving specific details of the input image.

Attribute Generative Adversarial Network +2

Shape from Polarization for Complex Scenes in the Wild

1 code implementation • CVPR 2022 • Chenyang Lei, Chenyang Qi, Jiaxin Xie, Na Fan, Vladlen Koltun, Qifeng Chen

We present a new data-driven approach with physics-based priors to scene-level normal estimation from a single polarization image.

Dual-Camera Super-Resolution with Aligned Attention Modules

2 code implementations • ICCV 2021 • Tengfei Wang, Jiaxin Xie, Wenxiu Sun, Qiong Yan, Qifeng Chen

We present a novel approach to reference-based super-resolution (RefSR) with the focus on dual-camera super-resolution (DCSR), which utilizes reference images for high-quality and high-fidelity results.

Domain Adaptation Reference-based Super-Resolution

Depth Sensing Beyond LiDAR Range

no code implementations • CVPR 2020 • Kai Zhang, Jiaxin Xie, Noah Snavely, Qifeng Chen

Depth sensing is a critical component of autonomous driving technologies, but today's LiDAR- or stereo camera-based solutions have limited range.

Autonomous Driving

Video Depth Estimation by Fusing Flow-to-Depth Proposals

1 code implementation • 30 Dec 2019 • Jiaxin Xie, Chenyang Lei, Zhuwen Li, Li Erran Li, Qifeng Chen

Our flow-to-depth layer is differentiable, and thus we can refine camera poses by maximizing the aggregated confidence in the camera pose refinement module.

Depth Estimation Optical Flow Estimation