15 code implementations • CVPR 2020 • Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, Oscar Beijbom
Most autonomous vehicles, however, carry a combination of cameras and range sensors such as lidar and radar.
Ranked #312 on 3D Object Detection on nuScenes (using extra training data)
1 code implementation • 30 Nov 2021 • Lingdong Kong, Niamul Quader, Venice Erin Liong
We present ConDA, a concatenation-based domain adaptation framework for LiDAR segmentation that: 1) constructs an intermediate domain consisting of fine-grained interchange signals from both source and target domains without destabilizing the semantic coherency of objects and background around the ego-vehicle; and 2) utilizes the intermediate domain for self-training.
no code implementations • CVPR 2015 • Venice Erin Liong, Jiwen Lu, Gang Wang, Pierre Moulin, Jie zhou
In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for large scale visual search.
no code implementations • ICCV 2015 • Jiwen Lu, Venice Erin Liong, Jie zhou
In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) method for face recognition.
no code implementations • ICCV 2017 • Venice Erin Liong, Jiwen Lu, Yap-Peng Tan, Jie zhou
In this paper, we propose a cross-modal deep variational hashing (CMDVH) method to learn compact binary codes for cross-modality multimedia retrieval.
no code implementations • 9 Dec 2020 • Venice Erin Liong, Thi Ngoc Tho Nguyen, Sergi Widjaja, Dhananjai Sharma, Zhuang Jie Chong
In this paper, we present an Assertion-based Multi-View Fusion network (AMVNet) for LiDAR semantic segmentation which aggregates the semantic features of individual projection-based networks using late fusion.
Ranked #14 on LIDAR Semantic Segmentation on nuScenes