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

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

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

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.

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