Search Results for author: Xiaofang Wang

Found 21 papers, 4 papers with code

Cost-Aware Evaluation and Model Scaling for LiDAR-Based 3D Object Detection

no code implementations2 May 2022 Xiaofang Wang, Kris M. Kitani

Considerable research efforts have been devoted to LiDAR-based 3D object detection and its empirical performance has been significantly improved.

3D Object Detection

Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains

no code implementations25 Feb 2022 Haitao Liu, Kai Wu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

Multi-task Gaussian process (MTGP) is a well-known non-parametric Bayesian model for learning correlated tasks effectively by transferring knowledge across tasks.

Dimensionality Reduction

Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization

no code implementations20 Sep 2021 Haitao Liu, Jiaqi Ding, Xinyu Xie, Xiaomo Jiang, Yusong Zhao, Xiaofang Wang

Multi-task regression attempts to exploit the task similarity in order to achieve knowledge transfer across related tasks for performance improvement.

Gaussian Processes Transfer Learning +1

Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems

no code implementations3 Jun 2021 Haitao Liu, Changjun Liu, Xiaomo Jiang, Xudong Chen, Shuhua Yang, Xiaofang Wang

Thereafter, we first investigate the methodological characteristics of the proposed deep probabilistic sequence model on toy cases, and then comprehensively demonstrate the superiority of our model against existing deep probabilistic SSM models through extensive numerical experiments on eight system identification benchmarks from various dynamic systems.

Probabilistic Time Series Forecasting Time Series

Neighborhood-Aware Neural Architecture Search

no code implementations13 May 2021 Xiaofang Wang, Shengcao Cao, Mengtian Li, Kris M. Kitani

To facilitate the application to gradient-based algorithms, we also propose a differentiable representation for the neighborhood of architectures.

Neural Architecture Search

Efficient Model Performance Estimation via Feature Histories

no code implementations7 Mar 2021 Shengcao Cao, Xiaofang Wang, Kris Kitani

Using a sampling-based search algorithm and parallel computing, our method can find an architecture which is better than DARTS and with an 80% reduction in wall-clock search time.

Image Classification Neural Architecture Search

Modulating Scalable Gaussian Processes for Expressive Statistical Learning

1 code implementation29 Aug 2020 Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

For a learning task, Gaussian process (GP) is interested in learning the statistical relationship between inputs and outputs, since it offers not only the prediction mean but also the associated variability.

Gaussian Processes Variational Inference

AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification

no code implementations ECCV 2020 Xiaofang Wang, Xuehan Xiong, Maxim Neumann, AJ Piergiovanni, Michael S. Ryoo, Anelia Angelova, Kris M. Kitani, Wei Hua

The discovered attention cells can be seamlessly inserted into existing backbone networks, e. g., I3D or S3D, and improve video classification accuracy by more than 2% on both Kinetics-600 and MiT datasets.

Classification General Classification +1

Deep Latent-Variable Kernel Learning

1 code implementation18 May 2020 Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

Deep kernel learning (DKL) leverages the connection between Gaussian process (GP) and neural networks (NN) to build an end-to-end, hybrid model.

Point in, Box out: Beyond Counting Persons in Crowds

no code implementations CVPR 2019 Yuting Liu, Miaojing Shi, Qijun Zhao, Xiaofang Wang

In the end, we propose a curriculum learning strategy to train the network from images of relatively accurate and easy pseudo ground truth first.

Crowd Counting

Learnable Embedding Space for Efficient Neural Architecture Compression

2 code implementations ICLR 2019 Shengcao Cao, Xiaofang Wang, Kris M. Kitani

We also demonstrate that the learned embedding space can be transferred to new settings for architecture search, such as a larger teacher network or a teacher network in a different architecture family, without any training.

Neural Architecture Search

Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning

no code implementations26 Sep 2018 Maxime Petit, Amaury Depierre, Xiaofang Wang, Emmanuel Dellandréa, Liming Chen

In simulation, we demonstrate the benefit of the transfer learning based on visual similarity, as opposed to an amnesic learning (i. e. learning from scratch all the time).

Bayesian Optimisation Transfer Learning

Error Correction Maximization for Deep Image Hashing

no code implementations6 Aug 2018 Xiang Xu, Xiaofang Wang, Kris M. Kitani

We propose to use the concept of the Hamming bound to derive the optimal criteria for learning hash codes with a deep network.

Image Registration Based Flicker Solving in Video Face Replacement and Analysis Based Sub-pixel Image Registration

no code implementations9 Mar 2018 Xiaofang Wang, Guoqiang Xiang, Xinyue Zhang, Wei Wei

In this paper, a framework of video face replacement is proposed and it deals with the flicker of swapped face in video sequence.

Image Registration

Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection

no code implementations9 Jan 2018 Yu-Xing Tang, Josiah Wang, Xiaofang Wang, Boyang Gao, Emmanuel Dellandrea, Robert Gaizauskas, Liming Chen

This is done by modeling the differences between the two on categories with both image-level and bounding box annotations, and transferring this information to convert classifiers to detectors for categories without bounding box annotations.

Object Detection Semi-Supervised Object Detection +1

Discriminative and Geometry Aware Unsupervised Domain Adaptation

no code implementations28 Dec 2017 Lingkun Luo, Liming Chen, Shiqiang Hu, Ying Lu, Xiaofang Wang

Domain adaptation (DA) aims to generalize a learning model across training and testing data despite the mismatch of their data distributions.

Image Classification Unsupervised Domain Adaptation

Robust Data Geometric Structure Aligned Close yet Discriminative Domain Adaptation

no code implementations24 May 2017 Lingkun Luo, Xiaofang Wang, Shiqiang Hu, Liming Chen

Domain adaptation (DA) is transfer learning which aims to leverage labeled data in a related source domain to achieve informed knowledge transfer and help the classification of unlabeled data in a target domain.

Domain Adaptation General Classification +2

Close Yet Distinctive Domain Adaptation

no code implementations13 Apr 2017 Lingkun Luo, Xiaofang Wang, Shiqiang Hu, Chao Wang, Yu-Xing Tang, Liming Chen

Most previous research tackle this problem in seeking a shared feature representation between source and target domains while reducing the mismatch of their data distributions.

Domain Adaptation Image Classification +1

Deep Supervised Hashing with Triplet Labels

1 code implementation12 Dec 2016 Xiaofang Wang, Yi Shi, Kris M. Kitani

The current state-of-the-art deep hashing method DPSH~\cite{li2015feature}, which is based on pairwise labels, performs image feature learning and hash code learning simultaneously by maximizing the likelihood of pairwise similarities.

Image Retrieval

Contextual Visual Similarity

no code implementations8 Dec 2016 Xiaofang Wang, Kris M. Kitani, Martial Hebert

Given a query image, a second positive image and a third negative image, dissimilar to the first two images, we define a contextualized similarity search criteria.

Image Retrieval Image Similarity Search

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