Shaohui Liu

DIST: Rendering with Differentiable Sphere Tracing

Shaohui Liu, , , , ,

CVPR, 2020.         Most work was done at .

[Project]  [arXiv]  [YouTube]  [BibTex] 

A new differentiable sphere tracing algorithm enables systems to efficiently render various 2D observations from deep implicit signed distance functions and effectively perform robust inverse optimization over 3D geometry with great generalization capability.

RepPoints: Point Set Representation for Object Detection

*, Shaohui Liu*, , ,

ICCV, 2019.         Intern project at .

[arXiv]  [Supplement]  [Slides]  [Chinese blogs 1 2 3]  [Code]  [BibTex] 

Using a set of representative points to connect stages for simultaneous semantically aligned feature extraction and flexible geometric 2D representation produces a brand new effective object recognition framework without the need of anchors and bounding boxes.

Normalized Diversification

Shaohui Liu*, *, ,

CVPR, 2019.        

[arXiv]  [Supplement]  [Slides]  [Code]  [BibTex] 

A novel loss term computed over the normalized pairwise distance matrices of the latent vectors and the corresponding outputs enforces both active extrapolation and safer interpolation of the mapping, ameliorating the notorious mode collapse problem on various vision applications.

Project August: Efficient Face Tracking at More than 1k FPS on CPU

Major project developer at in 2017.

[Project]  [YouTube] 

By caching, reusing and sharing intermediate features of a lightweight regression-based tracking model across frames we achieved extremely efficient face tracking and deployed the system onto real-world market products, as a preprocessing step for subsequent face analysis.