scispace - formally typeset
H

Hao Su

Researcher at University of California, San Diego

Publications -  364
Citations -  82843

Hao Su is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Computer science & Point cloud. The author has an hindex of 57, co-authored 302 publications receiving 55902 citations. Previous affiliations of Hao Su include Philips & Jiangxi University of Science and Technology.

Papers
More filters
Journal ArticleDOI

A Noncrystallization Approach toward Uniform Thylakoids-like 2D "Nano-coins" and Their Grana-like 3D Suprastructures.

TL;DR: A noncrystallization approach to achieve 2D nano-coins from assemblies of a set of zwitterionic giant surfactants is presented, which opens a door for controlling the shape, size, and size distribution of assembled nanostructures with different hierarchies.
Journal ArticleDOI

Learning hierarchical shape segmentation and labeling from online repositories

TL;DR: It is demonstrated that the proposed method for converting geometric shapes into hierarchically segmented parts with part labels can mine complex information, detecting hierarchies in man-made objects and their constituent parts, obtaining finer scale details than existing alternatives.
Posted ContentDOI

SofGAN: A Portrait Image Generator with Dynamic Styling

TL;DR: Wang et al. as discussed by the authors propose to separate the latent space of portrait images into two subspaces: a geometry space and a texture space, which are then fed to two network branches separately, one to generate the 3D geometry of portraits with canonical pose, and the other to generate textures.
Journal ArticleDOI

Supramolecular Tubustecan Hydrogel as Chemotherapeutic Carrier to Improve Tumor Penetration and Local Treatment Efficacy.

TL;DR: In vitro and in vivo studies reveal that these dual drug-bearing supramolecular hydrogels enhance tumor retention and penetration, serving as a local therapeutic depot for potent tumor regression, inhibition of tumor metastasis and recurrence, and mitigation of the off-target side effects.
Proceedings ArticleDOI

Multilinear Hyperplane Hashing

TL;DR: A multilinear hyperplane hashing that generates a hash bit using multiple linear projections with strong locality sensitivity to hyperplane queries is proposed and an angular quantization based learning framework for compact multil inear hashing is introduced, which considerably boosts the search performance with less hash bits.