Search Results for author: Kai Xu

Found 83 papers, 30 papers with code

RayMVSNet: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo

no code implementations4 Apr 2022 Junhua Xi, Yifei Shi, Yijie Wang, Yulan Guo, Kai Xu

In particular, we propose RayMVSNet which learns sequential prediction of a 1D implicit field along each camera ray with the zero-crossing point indicating scene depth.

Multi-Task Learning

Learning High-DOF Reaching-and-Grasping via Dynamic Representation of Gripper-Object Interaction

no code implementations3 Apr 2022 Qijin She, Ruizhen Hu, Juzhan Xu, Min Liu, Kai Xu, Hui Huang

To resolve the sample efficiency issue in learning the high-dimensional and complex control of dexterous grasping, we propose an effective representation of grasping state characterizing the spatial interaction between the gripper and the target object.

DisARM: Displacement Aware Relation Module for 3D Detection

no code implementations2 Mar 2022 Yao Duan, Chenyang Zhu, Yuqing Lan, Renjiao Yi, Xinwang Liu, Kai Xu

However, adopting relations between all the object or patch proposals for detection is inefficient, and an imbalanced combination of local and global relations brings extra noise that could mislead the training.

3D Object Detection

DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training

1 code implementation28 Feb 2022 Joya Chen, Kai Xu, Yifei Cheng, Angela Yao

The bulk of memory is occupied by caching intermediate tensors for gradient computation in the backward pass.

ARM3D: Attention-based relation module for indoor 3D object detection

1 code implementation20 Feb 2022 Yuqing Lan, Yao Duan, Chenyi Liu, Chenyang Zhu, Yueshan Xiong, Hui Huang, Kai Xu

In the field of 3D object detection, previous methods have been taking the advantage of context encoding, graph embedding, or explicit relation reasoning to extract relation context.

3D Object Detection Graph Embedding

3DRM:Pair-wise relation module for 3D object detection

1 code implementation20 Feb 2022 Yuqing Lan, Yao Duan, Yifei Shi, Hui Huang, Kai Xu

Context has proven to be one of the most important factors in object layout reasoning for 3D scene understanding.

3D Object Detection Scene Understanding

Geometric Transformer for Fast and Robust Point Cloud Registration

1 code implementation14 Feb 2022 Zheng Qin, Hao Yu, Changjian Wang, Yulan Guo, Yuxing Peng, Kai Xu

Such sparse and loose matching requires contextual features capturing the geometric structure of the point clouds.

Point Cloud Registration

RIM-Net: Recursive Implicit Fields for Unsupervised Learning of Hierarchical Shape Structures

no code implementations30 Jan 2022 Chengjie Niu, Manyi Li, Kai Xu, Hao Zhang

Each level of the tree corresponds to an assembly of shape parts, represented as implicit functions, to reconstruct the input shape.

STEdge: Self-training Edge Detection with Multi-layer Teaching and Regularization

no code implementations13 Jan 2022 Yunfan Ye, Renjiao Yi, Zhiping Cai, Kai Xu

In particular, we impose a consistency regularization which enforces the outputs from each of the multiple layers to be consistent for the input image and its perturbed counterpart.

Edge Detection Self-Supervised Learning

Box2Seg: Learning Semantics of 3D Point Clouds with Box-Level Supervision

no code implementations9 Jan 2022 Yan Liu, Qingyong Hu, Yinjie Lei, Kai Xu, Jonathan Li, Yulan Guo

In this paper, we introduce a neural architecture, termed Box2Seg, to learn point-level semantics of 3D point clouds with bounding box-level supervision.

Semantic Segmentation

Decoupling Makes Weakly Supervised Local Feature Better

1 code implementation8 Jan 2022 Kunhong Li, Longguang Wang, Li Liu, Qing Ran, Kai Xu, Yulan Guo

Weakly supervised learning can help local feature methods to overcome the obstacle of acquiring a large-scale dataset with densely labeled correspondences.

Camera Localization Image Matching

A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics

no code implementations NeurIPS 2021 Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer Ullman, Josh Tenenbaum, Charles Sutton

In this paper, we propose a Bayesian-symbolic framework (BSP) for physical reasoning and learning that is close to human-level sample-efficiency and accuracy.

Bayesian Inference Bilevel Optimization +1

Targeted Neural Dynamical Modeling

2 code implementations NeurIPS 2021 Cole Hurwitz, Akash Srivastava, Kai Xu, Justin Jude, Matthew G. Perich, Lee E. Miller, Matthias H. Hennig

These approaches, however, are limited in their ability to capture the underlying neural dynamics (e. g. linear) and in their ability to relate the learned dynamics back to the observed behaviour (e. g. no time lag).

Learning Efficient Online 3D Bin Packing on Packing Configuration Trees

1 code implementation ICLR 2022 Hang Zhao, Yang Yu, Kai Xu

PCT is a full-fledged description of the state and action space of bin packing which can support packing policy learning based on deep reinforcement learning (DRL).

3D Bin Packing

Repairing Systematic Outliers by Learning Clean Subspaces in VAEs

no code implementations29 Sep 2021 Simao Eduardo, Kai Xu, Alfredo Nazabal, Charles Sutton

Seeing as a systematic outlier is a combination of patterns of a clean instance and systematic error patterns, our main insight is that inliers can be modelled by a smaller representation (subspace) in a model than outliers.

Outlier Detection

Scaling Densities For Improved Density Ratio Estimation

no code implementations29 Sep 2021 Akash Srivastava, Seungwook Han, Benjamin Rhodes, Kai Xu, Michael U. Gutmann

As such, estimating density ratios accurately using only samples from $p$ and $q$ is of high significance and has led to a flurry of recent work in this direction.

Density Ratio Estimation

Learning Practically Feasible Policies for Online 3D Bin Packing

2 code implementations31 Aug 2021 Hang Zhao, Chenyang Zhu, Xin Xu, Hui Huang, Kai Xu

In this problem, the items are delivered to the agent without informing the full sequence information.

3D Bin Packing

Accelerating Video Object Segmentation with Compressed Video

1 code implementation26 Jul 2021 Kai Xu, Angela Yao

We propose an efficient plug-and-play acceleration framework for semi-supervised video object segmentation by exploiting the temporal redundancies in videos presented by the compressed bitstream.

Semantic Segmentation Semi-Supervised Video Object Segmentation +1

Objective-aware Traffic Simulation via Inverse Reinforcement Learning

no code implementations20 May 2021 Guanjie Zheng, Hanyang Liu, Kai Xu, Zhenhui Li

Traffic simulators act as an essential component in the operating and planning of transportation systems.

reinforcement-learning

ROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion

no code implementations12 May 2021 Jiazhao Zhang, Chenyang Zhu, Lintao Zheng, Kai Xu

We propose to tackle the difficulties of fast-motion camera tracking in the absence of inertial measurements using random optimization, in particular, the Particle Filter Optimization (PFO).

Pose Tracking

Potential Convolution: Embedding Point Clouds into Potential Fields

no code implementations5 Apr 2021 Dengsheng Chen, Haowen Deng, Jun Li, Duo Li, Yao Duan, Kai Xu

In this work, rather than defining a continuous or discrete kernel, we directly embed convolutional kernels into the learnable potential fields, giving rise to potential convolution.

3D Shape Classification Scene Segmentation

Learning Fine-Grained Segmentation of 3D Shapes without Part Labels

no code implementations CVPR 2021 Xiaogang Wang, Xun Sun, Xinyu Cao, Kai Xu, Bin Zhou

Learning-based 3D shape segmentation is usually formulated as a semantic labeling problem, assuming that all parts of training shapes are annotated with a given set of tags.

Deep Clustering

StablePose: Learning 6D Object Poses from Geometrically Stable Patches

no code implementations CVPR 2021 Yifei Shi, Junwen Huang, Xin Xu, Yifan Zhang, Kai Xu

According to the theory of geometric stability analysis, a minimal set of three planar/cylindrical patches are geometrically stable and determine the full 6DoFs of the object pose.

6D Pose Estimation using RGB Pose Prediction

Selective Sensing: A Data-driven Nonuniform Subsampling Approach for Computation-free On-Sensor Data Dimensionality Reduction

no code implementations1 Jan 2021 Zhikang Zhang, Kai Xu, Fengbo Ren

In this paper, we propose a selective sensing framework that adopts the novel concept of data-driven nonuniform subsampling to reduce the dimensionality of acquired signals while retaining the information of interest in a computation-free fashion.

Compressive Sensing Dimensionality Reduction +1

A Bayesian-Symbolic Approach to Learning and Reasoning for Intuitive Physics

no code implementations1 Jan 2021 Kai Xu, Akash Srivastava, Dan Gutfreund, Felix Sosa, Tomer Ullman, Joshua B. Tenenbaum, Charles Sutton

As such, learning the laws is then reduced to symbolic regression and Bayesian inference methods are used to obtain the distribution of unobserved properties.

Bayesian Inference Common Sense Reasoning

Study of charmonium-like and fully-charm tetraquark spectroscopy

no code implementations31 Dec 2020 Zheng Zhao, Kai Xu, Attaphon Kaewsnod, Xuyang Liu, Ayut Limphirat, Yupeng Yan

The masses of tetraquark states of all $qc\bar q \bar c$ and $cc\bar c \bar c$ quark configurations are evaluated in a constituent quark model, where the Cornell-like potential and one-gluon exchange spin-spin coupling are employed.

High Energy Physics - Phenomenology

Hausdorff Point Convolution with Geometric Priors

no code implementations24 Dec 2020 Pengdi Huang, Liqiang Lin, Fuyou Xue, Kai Xu, Danny Cohen-Or, Hui Huang

We show that HPC constitutes a powerful point feature learning with a rather compact set of only four types of geometric priors as kernels.

Semantic Segmentation

One Point is All You Need: Directional Attention Point for Feature Learning

no code implementations11 Dec 2020 Liqiang Lin, Pengdi Huang, Chi-Wing Fu, Kai Xu, Hao Zhang, Hui Huang

We present a novel attention-based mechanism for learning enhanced point features for tasks such as point cloud classification and segmentation.

Point Cloud Classification

A geometry-based relaxation algorithm for equilibrating a trivalent polygonal network in two dimensions and its implications

no code implementations5 Nov 2020 Kai Xu

The succeed of simulation strongly supports the ellipse packing hypothesis that was proposed to explain the dynamic behaviors of a trivalent 2D structure.

Biological Physics Adaptation and Self-Organizing Systems Cell Behavior

Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling

no code implementations25 Oct 2020 Akash Srivastava, Yamini Bansal, Yukun Ding, Cole Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund

Current autoencoder-based disentangled representation learning methods achieve disentanglement by penalizing the (aggregate) posterior to encourage statistical independence of the latent factors.

Disentanglement

WarpCore: A Library for fast Hash Tables on GPUs

1 code implementation16 Sep 2020 Daniel Jünger, Robin Kobus, André Müller, Christian Hundt, Kai Xu, Weiguo Liu, Bertil Schmidt

The rapidly growing amount of data emerging in many fields motivated the need for accelerated hash tables designed for modern parallel architectures.

Distributed, Parallel, and Cluster Computing

SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

no code implementations2 Aug 2020 Yifei Shi, Junwen Huang, Hongjia Zhang, Xin Xu, Szymon Rusinkiewicz, Kai Xu

We propose an end-to-end deep neural network which is able to predict both reflectional and rotational symmetries of 3D objects present in the input RGB-D image.

Multi-Task Learning Symmetry Detection

AReLU: Attention-based Rectified Linear Unit

1 code implementation24 Jun 2020 Dengsheng Chen, Jun Li, Kai Xu

Adding the attention module with a rectified linear unit (ReLU) results in an amplification of positive elements and a suppression of negative ones, both with learned, data-adaptive parameters.

Meta-Learning Transfer Learning

Fusion-Aware Point Convolution for Online Semantic 3D Scene Segmentation

1 code implementation CVPR 2020 Jiazhao Zhang, Chenyang Zhu, Lintao Zheng, Kai Xu

Online semantic 3D segmentation in company with real-time RGB-D reconstruction poses special challenges such as how to perform 3D convolution directly over the progressively fused 3D geometric data, and how to smartly fuse information from frame to frame.

Frame Scene Segmentation

Learning in the Frequency Domain

4 code implementations CVPR 2020 Kai Xu, Minghai Qin, Fei Sun, Yuhao Wang, Yen-Kuang Chen, Fengbo Ren

Experiment results show that learning in the frequency domain with static channel selection can achieve higher accuracy than the conventional spatial downsampling approach and meanwhile further reduce the input data size.

Instance Segmentation Semantic Segmentation

DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models

1 code implementation7 Feb 2020 Mohamed Tarek, Kai Xu, Martin Trapp, Hong Ge, Zoubin Ghahramani

Since DynamicPPL is a modular, stand-alone library, any probabilistic programming system written in Julia, such as Turing. jl, can use DynamicPPL to specify models and trace their model parameters.

Probabilistic Programming

Deep Differentiable Grasp Planner for High-DOF Grippers

no code implementations4 Feb 2020 Min Liu, Zherong Pan, Kai Xu, Kanishka Ganguly, Dinesh Manocha

We present an end-to-end algorithm for training deep neural networks to grasp novel objects.

Robotics

Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation

no code implementations CVPR 2020 Dengsheng Chen, Jun Li, Zheng Wang, Kai Xu

To tackle intra-class shape variations, we learn canonical shape space (CASS), a unified representation for a large variety of instances of a certain object category.

3D Shape Representation Generating 3D Point Clouds

Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering

no code implementations17 Dec 2019 Kai Xu, Xiao-Jun Wu, Wen-Bo Hu

Based on further studying the low-rank subspace clustering (LRSC) and L2-graph subspace clustering algorithms, we propose a F-graph subspace clustering algorithm with a symmetric constraint (FSSC), which constructs a new objective function with a symmetric constraint basing on F-norm, whose the most significant advantage is to obtain a closed-form solution of the coefficient matrix.

Face Clustering Motion Segmentation

Reinforcement Learning-based Visual Navigation with Information-Theoretic Regularization

1 code implementation9 Dec 2019 Qiaoyun Wu, Kai Xu, Jun Wang, Mingliang Xu, Dinesh Manocha

The regularization maximizes the mutual information between navigation actions and visual observation transforms of an agent, thus promoting more informed navigation decisions.

Robotics

Decoupling Features and Coordinates for Few-shot RGB Relocalization

no code implementations26 Nov 2019 Siyan Dong, Songyin Wu, Yixin Zhuang, Kai Xu, Shanghang Zhang, Baoquan Chen

To address this issue, we approach camera relocalization with a decoupled solution where feature extraction, coordinate regression, and pose estimation are performed separately.

Camera Relocalization Pose Estimation

AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms

1 code implementation pproximateinference AABI Symposium 2019 Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani

Stan's Hamilton Monte Carlo (HMC) has demonstrated remarkable sampling robustness and efficiency in a wide range of Bayesian inference problems through carefully crafted adaption schemes to the celebrated No-U-Turn sampler (NUTS) algorithm.

Bayesian Inference

Rescan: Inductive Instance Segmentation for Indoor RGBD Scans

no code implementations ICCV 2019 Maciej Halber, Yifei Shi, Kai Xu, Thomas Funkhouser

In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e. g., as part of regular daily use).

Instance Segmentation Semantic Segmentation

Building change detection based on multi-scale filtering and grid partition

no code implementations22 Aug 2019 Qi Bi, Kun Qin, Han Zhang, Wenjun Han, Zhili Li, Kai Xu

Exhaustive experiments indicate that the proposed method can detect building change types directly and outperform the current multi-index learning method.

Change Detection

Multiple instance dense connected convolution neural network for aerial image scene classification

no code implementations22 Aug 2019 Qi Bi, Kun Qin, Zhili Li, Han Zhang, Kai Xu

While the current convolution neural network tends to extract global features and global semantic information in a scene, the geo-spatial objects can be located at anywhere in an aerial image scene and their spatial arrangement tends to be more complicated.

General Classification Scene Classification

Active Scene Understanding via Online Semantic Reconstruction

no code implementations18 Jun 2019 Lintao Zheng, Chenyang Zhu, Jiazhao Zhang, Hang Zhao, Hui Huang, Matthias Niessner, Kai Xu

In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene.

Scene Understanding Semantic Segmentation

NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations

1 code implementation17 Jun 2019 Qiaoyun Wu, Dinesh Manocha, Jun Wang, Kai Xu

First, the latent distribution is conditioned on current observations and the target view, leading to a model-based, target-driven navigation.

Visual Navigation

Learning Part Generation and Assembly for Structure-aware Shape Synthesis

no code implementations16 Jun 2019 Jun Li, Chengjie Niu, Kai Xu

Enlightened by the fact that 3D shape structure is characterized as part composition and placement, we propose to model 3D shape variations with a part-aware deep generative network, coined as PAGENet.

Diagnosing Reinforcement Learning for Traffic Signal Control

no code implementations12 May 2019 Guanjie Zheng, Xinshi Zang, Nan Xu, Hua Wei, Zhengyao Yu, Vikash Gayah, Kai Xu, Zhenhui Li

In this paper, we propose to re-examine the RL approaches through the lens of classic transportation theory.

reinforcement-learning

Learning Phase Competition for Traffic Signal Control

1 code implementation12 May 2019 Guanjie Zheng, Yuanhao Xiong, Xinshi Zang, Jie Feng, Hua Wei, Huichu Zhang, Yong Li, Kai Xu, Zhenhui Li

Increasingly available city data and advanced learning techniques have empowered people to improve the efficiency of our city functions.

CoLight: Learning Network-level Cooperation for Traffic Signal Control

3 code implementations11 May 2019 Hua Wei, Nan Xu, Huichu Zhang, Guanjie Zheng, Xinshi Zang, Chacha Chen, Wei-Nan Zhang, Yanmin Zhu, Kai Xu, Zhenhui Li

To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication.

Multi-agent Reinforcement Learning

Spatiotemporal CNN for Video Object Segmentation

1 code implementation CVPR 2019 Kai Xu, Longyin Wen, Guorong Li, Liefeng Bo, Qingming Huang

Specifically, the temporal coherence branch pretrained in an adversarial fashion from unlabeled video data, is designed to capture the dynamic appearance and motion cues of video sequences to guide object segmentation.

Semantic Segmentation Semi-Supervised Video Object Segmentation +3

AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss

no code implementations CVPR 2020 Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Li Yi, Leonidas Guibas, Hao Zhang

While the part prior network can be trained with noisy and inconsistently segmented shapes, the final output of AdaCoSeg is a consistent part labeling for the input set, with each shape segmented into up to (a user-specified) K parts.

Instance Segmentation Semantic Segmentation

Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapes

1 code implementation CVPR 2019 Xiaogang Wang, Bin Zhou, Yahao Shi, Xiaowu Chen, Qinping Zhao, Kai Xu

For the task of mobility analysis of 3D shapes, we propose joint analysis for simultaneous motion part segmentation and motion attribute estimation, taking a single 3D model as input.

PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation

no code implementations CVPR 2019 Fenggen Yu, Kun Liu, Yan Zhang, Chenyang Zhu, Kai Xu

Meanwhile, to increase the segmentation accuracy at each node, we enhance the recursive contextual feature with the shape feature extracted for the corresponding part.

3D Instance Segmentation 3D Part Segmentation

Generating Grasp Poses for a High-DOF Gripper Using Neural Networks

no code implementations1 Mar 2019 Min Liu, Zherong Pan, Kai Xu, Kanishka Ganguly, Dinesh Manocha

The quality of the grasp poses is on par with the groundtruth poses in the dataset.

Robotics

SCORES: Shape Composition with Recursive Substructure Priors

no code implementations14 Sep 2018 Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Renjiao Yi, Hao Zhang

The network may significantly alter the geometry and structure of the input parts and synthesize a novel shape structure based on the inputs, while adding or removing parts to minimize a structure plausibility loss.

Learning to Group and Label Fine-Grained Shape Components

no code implementations13 Sep 2018 Xiaogang Wang, Bin Zhou, Haiyue Fang, Xiaowu Chen, Qinping Zhao, Kai Xu

We propose to generate part hypotheses from the components based on a hierarchical grouping strategy, and perform labeling on those part groups instead of directly on the components.

Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets

no code implementations20 Aug 2018 Yawei Zhao, Kai Xu, Xinwang Liu, En Zhu, Xinzhong Zhu, Jianping Yin

The reason is that it finds the similar instances according to their features directly, which is usually impacted by the imperfect data, and thus returns sub-optimal results.

Learning Discriminative 3D Shape Representations by View Discerning Networks

2 code implementations11 Aug 2018 Biao Leng, Cheng Zhang, Xiaocheng Zhou, Cheng Xu, Kai Xu

In this network, a Score Generation Unit is devised to evaluate the quality of each projected image with score vectors.

3D Shape Recognition 3D Shape Representation

GRAINS: Generative Recursive Autoencoders for INdoor Scenes

no code implementations24 Jul 2018 Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, Hao Zhang

We present a generative neural network which enables us to generate plausible 3D indoor scenes in large quantities and varieties, easily and highly efficiently.

Graphics

LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction

1 code implementation ECCV 2018 Kai Xu, Zhikang Zhang, Fengbo Ren

We propose a scalable Laplacian pyramid reconstructive adversarial network (LAPRAN) that enables high-fidelity, flexible and fast CS images reconstruction.

Compressive Sensing SSIM

Generative Ratio Matching Networks

no code implementations ICLR 2020 Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton

In this work, we take their insight of using kernels as fixed adversaries further and present a novel method for training deep generative models that does not involve saddlepoint optimization.

Semi-Supervised Co-Analysis of 3D Shape Styles from Projected Lines

no code implementations18 Apr 2018 Fenggen Yu, Yan Zhang, Kai Xu, Ali Mahdavi-Amiri, Hao Zhang

We present a semi-supervised co-analysis method for learning 3D shape styles from projected feature lines, achieving style patch localization with only weak supervision.

Im2Struct: Recovering 3D Shape Structure from a Single RGB Image

no code implementations CVPR 2018 Chengjie Niu, Jun Li, Kai Xu

We propose to recover 3D shape structures from single RGB images, where structure refers to shape parts represented by cuboids and part relations encompassing connectivity and symmetry.

PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction

no code implementations ECCV 2018 Yifei Shi, Kai Xu, Matthias Niessner, Szymon Rusinkiewicz, Thomas Funkhouser

We introduce a novel RGB-D patch descriptor designed for detecting coplanar surfaces in SLAM reconstruction.

Interpreting Deep Classifier by Visual Distillation of Dark Knowledge

no code implementations11 Mar 2018 Kai Xu, Dae Hoon Park, Chang Yi, Charles Sutton

Interpreting black box classifiers, such as deep networks, allows an analyst to validate a classifier before it is deployed in a high-stakes setting.

Dimensionality Reduction Model Compression

GRASS: Generative Recursive Autoencoders for Shape Structures

no code implementations5 May 2017 Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, Leonidas Guibas

We introduce a novel neural network architecture for encoding and synthesis of 3D shapes, particularly their structures.

A GPU-Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks

no code implementations20 Feb 2017 Yixing Li, Zichuan Liu, Kai Xu, Hao Yu, Fengbo Ren

For processing static data in large batch sizes, the proposed solution is on a par with a Titan X GPU in terms of throughput while delivering 9. 5x higher energy efficiency.

A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing

no code implementations15 Dec 2016 Kai Xu, Yixing Li, Fengbo Ren

Compressive sensing (CS) is a promising technology for realizing energy-efficient wireless sensors for long-term health monitoring.

Compressive Sensing

CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive Sensing

2 code implementations15 Dec 2016 Kai Xu, Fengbo Ren

This paper addresses the real-time encoding-decoding problem for high-frame-rate video compressive sensing (CS).

Compressive Sensing Frame +1

Recurrent 3D Attentional Networks for End-to-End Active Object Recognition

no code implementations14 Oct 2016 Min Liu, Yifei Shi, Lintao Zheng, Kai Xu, Hui Huang, Dinesh Manocha

Active vision is inherently attention-driven: The agent actively selects views to attend in order to fast achieve the vision task while improving its internal representation of the scene being observed.

Object Recognition

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