
MOTChallenge: A Benchmark for Singlecamera Multiple Target Tracking
Standardized benchmarks have been crucial in pushing the performance of ...
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LMReloc: LevenbergMarquardt Based Direct Visual Relocalization
We present LMReloc – a novel approach for visual relocalization based o...
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4Seasons: A CrossSeason Dataset for MultiWeather SLAM in Autonomous Driving
We present a novel dataset covering seasonal and challenging perceptual ...
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DH3D: Deep Hierarchical 3D Descriptors for Robust LargeScale 6DoF Relocalization
For relocalization in largescale point clouds, we propose the first app...
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Deriving Neural Network Design and Learning from the Probabilistic Framework of Chain Graphs
The last decade has witnessed a boom of neural network (NN) research and...
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Effective Version Space Reduction for Convolutional Neural Networks
In active learning, sampling bias could pose a serious inconsistency pro...
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PrimiTect: Fast Continuous Hough Voting for Primitive Detection
This paper tackles the problem of data abstraction in the context of 3D ...
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Hamiltonian Dynamics for RealWorld Shape Interpolation
We revisit the classical problem of 3D shape interpolation and propose a...
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MOT20: A benchmark for multi object tracking in crowded scenes
Standardized benchmarks are crucial for the majority of computer vision ...
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D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
We propose D3VO as a novel framework for monocular visual odometry that ...
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Optimization of Graph Total Variation via ActiveSetbased Combinatorial Reconditioning
Structured convex optimization on weighted graphs finds numerous applica...
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Learn to Predict Sets Using FeedForward Neural Networks
This paper addresses the task of set prediction using deep feedforward ...
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From Planes to Corners: MultiPurpose Primitive Detection in Unorganized 3D Point Clouds
We propose a new method for segmentationfree joint estimation of orthog...
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Inferring SuperResolution Depth from a Moving LightSource Enhanced RGBD Sensor: A Variational Approach
A novel approach towards depth map superresolution using multiview unc...
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Informative GANs via Structured Regularization of Optimal Transport
We tackle the challenge of disentangled representation learning in gener...
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Efficient Derivative Computation for Cumulative BSplines on Lie Groups
Continuoustime trajectory representation has recently gained popularity...
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On the wellposedness of uncalibrated photometric stereo under general lighting
Uncalibrated photometric stereo aims at estimating the 3Dshape of a sur...
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RollingShutter Modelling for Direct VisualInertial Odometry
We present a direct visualinertial odometry (VIO) method which estimate...
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Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods
One of the reasons for the success of convolutional networks is their eq...
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MultiFrame GAN: Image Enhancement for Stereo Visual Odometry in Low Light
We propose the concept of a multiframe GAN (MFGAN) and demonstrate its ...
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Bregman Proximal Framework for Deep Linear Neural Networks
A typical assumption for the analysis of first order optimization method...
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Sparse Surface Constraints for Combining Physicsbased Elasticity Simulation and CorrespondenceFree Object Reconstruction
We address the problem to infer physical material parameters and boundar...
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Lifting methods for manifoldvalued variational problems
Lifting methods allow to transform hard variational problems such as seg...
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Towards Generalizing Sensorimotor Control Across Weather Conditions
The ability of deep learning models to generalize well across different ...
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CVPR19 Tracking and Detection Challenge: How crowded can it get?
Standardized benchmarks are crucial for the majority of computer vision ...
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Smooth Shells: MultiScale Shape Registration with Functional Maps
We propose a novel 3D shape correspondence method based on the iterative...
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Flat Metric Minimization with Applications in Generative Modeling
We take the novel perspective to view data not as a probability distribu...
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Learning to Evolve
Evolution and learning are two of the fundamental mechanisms by which li...
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Lifting Vectorial Variational Problems: A Natural Formulation based on Geometric Measure Theory and Discrete Exterior Calculus
Numerous tasks in imaging and vision can be formulated as variational pr...
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GNNet: The GaussNewton Loss for Deep Direct SLAM
Direct methods for SLAM have shown exceptional performance on odometry t...
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DirectShape: Photometric Alignment of Shape Priors for Visual Vehicle Pose and Shape Estimation
3D scene understanding from images is a challenging problem which is enc...
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VisualInertial Mapping with NonLinear Factor Recovery
Cameras and inertial measurement units are complementary sensors for ego...
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Variational Uncalibrated Photometric Stereo under General Lighting
Photometric stereo (PS) techniques nowadays remain constrained to an ide...
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Controlling Neural Networks via Energy Dissipation
The last decade has shown a tremendous success in solving various comput...
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Optimization of InfConvolution Regularized Nonconvex Composite Problems
In this work, we consider nonconvex composite problems that involve inf...
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Linear Inequality Constraints for Neural Network Activations
We propose a method to impose linear inequality constraints on neural ne...
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Probabilistic Discriminative Learning with Layered Graphical Models
Probabilistic graphical models are traditionally known for their success...
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Photometric Depth SuperResolution
This study explores the use of photometric techniques (shapefromshadin...
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DeepWrinkles: Accurate and Realistic Clothing Modeling
We present a novel method to generate accurate and realistic clothing de...
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Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras
We propose a novel realtime direct monocular visual odometry for omnidi...
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Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform
Dense pixelwise prediction such as semantic segmentation is an uptodat...
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LDSO: Direct Sparse Odometry with Loop Closure
In this paper we present an extension of Direct Sparse Odometry (DSO) to...
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Direct Sparse Odometry with Rolling Shutter
Neglecting the effects of rollingshutter cameras for visual odometry (V...
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The Double Sphere Camera Model
Visionbased motion estimation and 3D reconstruction, which have numerou...
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Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry
Monocular visual odometry approaches that purely rely on geometric cues ...
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A GaussNewton Approach to RealTime Monocular Multiple Object Tracking
We propose an algorithm for realtime 6DOF pose tracking of rigid 3D obj...
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Modular Vehicle Control for Transferring Semantic Information to Unseen Weather Conditions using GANs
Endtoend supervised learning has shown promising results for selfdriv...
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DivergenceFree Shape Interpolation and Correspondence
We present a novel method to model and calculate deformation fields betw...
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qSpace Novelty Detection with Variational Autoencoders
In machine learning, novelty detection is the task of identifying novel ...
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Deep PermSet Net: Learn to Predict Sets with Unknown Permutation and Cardinality Using Deep Neural Networks
We present a novel approach for learning to predict sets with unknown pe...
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