Search Results for author: Gim Hee Lee

Found 48 papers, 34 papers with code

Relative Pose Estimation of Calibrated Cameras with Known SE(3) Invariants

1 code implementation ECCV 2020 Bo Li, Evgeniy Martyushev, Gim Hee Lee

In this paper, we present a complete comprehensive study of the relative pose estimation problem for a calibrated camera constrained by known $\mathrm{SE}(3)$ invariant, which involves 5 minimal problems in total.

Pose Estimation Translation

Voxel-based Network for Shape Completion by Leveraging Edge Generation

1 code implementation ICCV 2021 Xiaogang Wang, Marcelo H Ang Jr, Gim Hee Lee

Deep learning technique has yielded significant improvements in point cloud completion with the aim of completing missing object shapes from partial inputs.

Point Cloud Completion

Source-Free Open Compound Domain Adaptation in Semantic Segmentation

no code implementations7 Jun 2021 Yuyang Zhao, Zhun Zhong, Zhiming Luo, Gim Hee Lee, Nicu Sebe

Second, CPSS can reduce the influence of noisy pseudo-labels and also avoid the model overfitting to the target domain during self-supervised learning, consistently boosting the performance on the target and open domains.

Domain Generalization Self-Supervised Learning +1

FILTRA: Rethinking Steerable CNN by Filter Transform

1 code implementation25 May 2021 Bo Li, Qili Wang, Gim Hee Lee

It has been an intuitive and widely used technique to construct a steerable filter by augmenting a filter with its transformed copies in the past decades, which is named as filter transform in this paper.

DeepI2P: Image-to-Point Cloud Registration via Deep Classification

1 code implementation CVPR 2021 Jiaxin Li, Gim Hee Lee

This paper presents DeepI2P: a novel approach for cross-modality registration between an image and a point cloud.

Classification General Classification +1

Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo

1 code implementation CVPR 2021 Jiahao Lin, Gim Hee Lee

Existing approaches for multi-view multi-person 3D pose estimation explicitly establish cross-view correspondences to group 2D pose detections from multiple camera views and solve for the 3D pose estimation for each person.

3D Pose Estimation Depth Estimation

Learning Spatial Context with Graph Neural Network for Multi-Person Pose Grouping

1 code implementation6 Apr 2021 Jiahao Lin, Gim Hee Lee

More specifically, we design a Geometry-aware Association GNN that utilizes spatial information of the keypoints and learns local affinity from the global context.

graph partitioning Keypoint Detection +1

MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis

1 code implementation ICCV 2021 Jiaxin Li, Zijian Feng, Qi She, Henghui Ding, Changhu Wang, Gim Hee Lee

In this paper, we propose MINE to perform novel view synthesis and depth estimation via dense 3D reconstruction from a single image.

3D Reconstruction Depth Estimation +1

From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation

1 code implementation CVPR 2021 Chen Li, Gim Hee Lee

Existing works circumvent this problem with pseudo labels generated from data of other easily accessible domains such as synthetic data.

Animal Pose Estimation Unsupervised Domain Adaptation

City-scale Scene Change Detection using Point Clouds

no code implementations26 Mar 2021 Zi Jian Yew, Gim Hee Lee

We propose a method for detecting structural changes in a city using images captured from vehicular mounted cameras over traversals at two different times.

Scene Change Detection Structure from Motion

Cascaded Refinement Network for Point Cloud Completion with Self-supervision

1 code implementation17 Oct 2020 Xiaogang Wang, Marcelo H Ang Jr, Gim Hee Lee

This is to mitigate the dependence of existing approaches on large amounts of ground truth training data that are often difficult to obtain in real-world applications.

3D Object Classification Object Classification +1

Weakly Supervised Generative Network for Multiple 3D Human Pose Hypotheses

1 code implementation13 Aug 2020 Chen Li, Gim Hee Lee

In this paper, we propose a weakly supervised deep generative network to address the inverse problem and circumvent the need for ground truth 2D-to-3D correspondences.

Multi-Hypotheses 3D Human Pose Estimation

Point Cloud Completion by Learning Shape Priors

1 code implementation2 Aug 2020 Xiaogang Wang, Marcelo H. Ang Jr, Gim Hee Lee

Then we learn a mapping to transfer the point features from partial points to that of the complete points by optimizing feature alignment losses.

Point Cloud Completion

HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

1 code implementation ECCV 2020 Jiahao Lin, Gim Hee Lee

Current works on multi-person 3D pose estimation mainly focus on the estimation of the 3D joint locations relative to the root joint and ignore the absolute locations of each pose.

3D Multi-Person Pose Estimation (absolute) 3D Multi-Person Pose Estimation (root-relative) +3

Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation

2 code implementations ECCV 2020 Meng Tian, Marcelo H. Ang Jr, Gim Hee Lee

We present a novel learning approach to recover the 6D poses and sizes of unseen object instances from an RGB-D image.

Relative Pose Estimation of Calibrated Cameras with Known $\mathrm{SE}(3)$ Invariants

no code implementations15 Jul 2020 Bo Li, Evgeniy Martyushev, Gim Hee Lee

In this paper, we present a complete comprehensive study of the relative pose estimation problem for a calibrated camera constrained by known $\mathrm{SE}(3)$ invariant, which involves 5 minimal problems in total.

Pose Estimation Translation

Few-shot 3D Point Cloud Semantic Segmentation

1 code implementation CVPR 2021 Na Zhao, Tat-Seng Chua, Gim Hee Lee

These fully supervised approaches heavily rely on large amounts of labeled training data that are difficult to obtain and cannot segment new classes after training.

Semantic Segmentation

Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer Labels

1 code implementation8 Apr 2020 Xun Xu, Gim Hee Lee

Point cloud analysis has received much attention recently; and segmentation is one of the most important tasks.

Point Cloud Segmentation

RPM-Net: Robust Point Matching using Learned Features

3 code implementations CVPR 2020 Zi Jian Yew, Gim Hee Lee

The hard assignments of closest point correspondences based on spatial distances are sensitive to the initial rigid transformation and noisy/outlier points, which often cause ICP to converge to wrong local minima.

Point Cloud Registration

Robust 6D Object Pose Estimation by Learning RGB-D Features

1 code implementation29 Feb 2020 Meng Tian, Liang Pan, Marcelo H. Ang Jr, Gim Hee Lee

Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping.

6D Pose Estimation using RGB

SESS: Self-Ensembling Semi-Supervised 3D Object Detection

1 code implementation CVPR 2020 Na Zhao, Tat-Seng Chua, Gim Hee Lee

The performance of existing point cloud-based 3D object detection methods heavily relies on large-scale high-quality 3D annotations.

3D Object Detection Semi-Supervised Image Classification

Identifying through Flows for Recovering Latent Representations

2 code implementations ICLR 2020 Shen Li, Bryan Hooi, Gim Hee Lee

Yet, most deep generative models do not address the question of identifiability, and thus fail to deliver on the promise of the recovery of the true latent sources that generate the observations.

Representation Learning

Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation

1 code implementation22 Aug 2019 Jiahao Lin, Gim Hee Lee

Although existing CNN-based temporal frameworks attempt to address the sensitivity and drift problems by concurrently processing all input frames in the sequence, the existing state-of-the-art CNN-based framework is limited to 3d pose estimation of a single frame from a sequential input.

3D Pose Estimation Monocular 3D Human Pose Estimation

PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation

1 code implementation15 Aug 2019 Na Zhao, Tat-Seng Chua, Gim Hee Lee

In this paper, we present the PS^2-Net -- a locally and globally aware deep learning framework for semantic segmentation on 3D scene-level point clouds.

Scene Segmentation

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

1 code implementation23 Jul 2019 Liang Pan, Chee-Meng Chew, Gim Hee Lee

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds.

Robust Point Cloud Based Reconstruction of Large-Scale Outdoor Scenes

1 code implementation CVPR 2019 Ziquan Lan, Zi Jian Yew, Gim Hee Lee

Furthermore, we show that by using a Gaussian-Uniform mixture model, our approach degenerates to the formulation of a state-of-the-art approach for robust indoor reconstruction.

3D Reconstruction

Transferable Semi-supervised 3D Object Detection from RGB-D Data

no code implementations ICCV 2019 Yew Siang Tang, Gim Hee Lee

We investigate the direction of training a 3D object detector for new object classes from only 2D bounding box labels of these new classes, while simultaneously transferring information from 3D bounding box labels of the existing classes.

3D Object Detection

2D3D-MatchNet: Learning to Match Keypoints Across 2D Image and 3D Point Cloud

no code implementations22 Apr 2019 Mengdan Feng, Sixing Hu, Marcelo Ang, Gim Hee Lee

Large-scale point cloud generated from 3D sensors is more accurate than its image-based counterpart.

Pose Estimation

Discrete Rotation Equivariance for Point Cloud Recognition

1 code implementation31 Mar 2019 Jiaxin Li, Yingcai Bi, Gim Hee Lee

In this paper, we propose a deep learning architecture that achieves discrete $\mathbf{SO}(2)$/$\mathbf{SO}(3)$ rotation equivariance for point cloud recognition.

USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds

1 code implementation ICCV 2019 Jiaxin Li, Gim Hee Lee

In this paper, we propose the USIP detector: an Unsupervised Stable Interest Point detector that can detect highly repeatable and accurately localized keypoints from 3D point clouds under arbitrary transformations without the need for any ground truth training data.

Interest Point Detection

Rolling-Shutter-Aware Differential SfM and Image Rectification

no code implementations ICCV 2017 Bingbing Zhuang, Loong-Fah Cheong, Gim Hee Lee

We demonstrate that the dense depth maps recovered from the relative pose of the RS camera can be used in a RS-aware warping for image rectification to recover high-quality Global Shutter (GS) images.

3D Reconstruction Optical Flow Estimation +3

Image-Based Geo-Localization Using Satellite Imagery

no code implementations1 Mar 2019 Sixing Hu, Gim Hee Lee

The problem of localization on a geo-referenced satellite map given a query ground view image is useful yet remains challenging due to the drastic change in viewpoint.

Baseline Desensitizing In Translation Averaging

no code implementations CVPR 2018 Bingbing Zhuang, Loong-Fah Cheong, Gim Hee Lee

Many existing translation averaging algorithms are either sensitive to disparate camera baselines and have to rely on extensive preprocessing to improve the observed Epipolar Geometry graph, or if they are robust against disparate camera baselines, require complicated optimization to minimize the highly nonlinear angular error objective.


3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration

1 code implementation ECCV 2018 Zi Jian Yew, Gim Hee Lee

In this paper, we propose the 3DFeat-Net which learns both 3D feature detector and descriptor for point cloud matching using weak supervision.

Point Cloud Registration

Solving the Perspective-2-Point Problem for Flying-Camera Photo Composition

no code implementations CVPR 2018 Ziquan Lan, David Hsu, Gim Hee Lee

The user, instead of holding a camera in hand and manually searching for a viewpoint, will interact directly with image contents in the viewfinder through simple gestures, and the flying camera will achieve the desired viewpoint through the autonomous flying capability of the drone.

CVM-Net: Cross-View Matching Network for Image-Based Ground-to-Aerial Geo-Localization

1 code implementation CVPR 2018 Sixing Hu, Mengdan Feng, Rang M. H. Nguyen, Gim Hee Lee

The problem of localization on a geo-referenced aerial/satellite map given a query ground view image remains challenging due to the drastic change in viewpoint that causes traditional image descriptors based matching to fail.

Metric Learning

PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition

7 code implementations CVPR 2018 Mikaela Angelina Uy, Gim Hee Lee

This is largely due to the difficulty in extracting local feature descriptors from a point cloud that can subsequently be encoded into a global descriptor for the retrieval task.

Point Cloud Retrieval Visual Place Recognition

SO-Net: Self-Organizing Network for Point Cloud Analysis

3 code implementations CVPR 2018 Jiaxin Li, Ben M. Chen, Gim Hee Lee

This paper presents SO-Net, a permutation invariant architecture for deep learning with orderless point clouds.

Ranked #33 on 3D Part Segmentation on ShapeNet-Part (Instance Average IoU metric)

3D Part Segmentation 3D Point Cloud Classification

Sparse to Dense 3D Reconstruction From Rolling Shutter Images

no code implementations CVPR 2016 Olivier Saurer, Marc Pollefeys, Gim Hee Lee

It is well known that the rolling shutter effect in images captured with a moving rolling shutter camera causes inaccuracies to 3D reconstructions.

3D Reconstruction

Relative Pose Estimation for a Multi-Camera System with Known Vertical Direction

no code implementations CVPR 2014 Gim Hee Lee, Marc Pollefeys, Friedrich Fraundorfer

In this paper, we present our minimal 4-point and linear 8-point algorithms to estimate the relative pose of a multi-camera system with known vertical directions, i. e. known absolute roll and pitch angles.

Pose Estimation

Motion Estimation for Self-Driving Cars with a Generalized Camera

no code implementations CVPR 2013 Gim Hee Lee, Friedrich Faundorfer, Marc Pollefeys

By modeling the multicamera system as a generalized camera and applying the non-holonomic motion constraint of a car, we show that this leads to a novel 2-point minimal solution for the generalized essential matrix where the full relative motion including metric scale can be obtained.

Motion Estimation Self-Driving Cars

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