42 citations · 57 across the 14 of their papers we have counts for
14 papers
4DRecons: 4D Neural Implicit Deformable Objects Reconstruction from a single RGB-D Camera with Geometrical and Topological Regularizations
Xiaoyan Cong, Haitao Yang, Liyan Chen +4
This paper presents a novel approach 4DRecons that takes a single camera RGB-D sequence of a dynamic subject as input and outputs a complete textured deforming 3D model over time.…
GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
Haitao Yang, Xiangru Huang, Bo Sun +2
This paper introduces GenCorres, a novel unsupervised joint shape matching (JSM) approach. Our key idea is to learn a mesh generator to fit an unorganized deformable shape collecti…
DeblurSR: Event-Based Motion Deblurring Under the Spiking Representation
Chen Song, Chandrajit Bajaj, Qixing Huang
We present DeblurSR, a novel motion deblurring approach that converts a blurry image into a sharp video. DeblurSR utilizes event data to compensate for motion ambiguities and explo…
Reinforcement Learning for Molecular Dynamics Optimization: A Stochastic Pontryagin Maximum Principle Approach
Chandrajit Bajaj, Minh Nguyen, Conrad Li
In this paper, we present a novel reinforcement learning framework designed to optimize molecular dynamics by focusing on the entire trajectory rather than just the final molecular…
A Particle-based Sparse Gaussian Process Optimizer
Chandrajit Bajaj, Omatharv Bharat Vaidya, Yi Wang
Task learning in neural networks typically requires finding a globally optimal minimizer to a loss function objective. Conventional designs of swarm based optimization methods appl…
Sample Efficient Learning of Factored Embeddings of Tensor Fields
Taemin Heo, Chandrajit Bajaj
Data tensors of orders 2 and greater are now routinely being generated. These data collections are increasingly huge and growing. Many scientific and medical data tensors are tenso…
E-CIR: Event-Enhanced Continuous Intensity Recovery
Chen Song, Qixing Huang, Chandrajit Bajaj
A camera begins to sense light the moment we press the shutter button. During the exposure interval, relative motion between the scene and the camera causes motion blur, a common u…
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation
Jan-Christopher Cohrs, Chandrajit Bajaj, Benjamin Berkels
Hyperspectral images provide a rich representation of the underlying spectrum for each pixel, allowing for a pixel-wise classification/segmentation into different classes. As the a…
Reinforcement Learning of Self Enhancing Camera Image and Signal Processing
Chandrajit Bajaj, Yi Wang, Yunhao Yang
Current camera image and signal processing pipelines (ISPs), including deep-trained versions, tend to apply a single filter that is uniformly applied to the entire image. This is d…
Recipes for when Physics Fails: Recovering Robust Learning of Physics Informed Neural Networks
Chandrajit Bajaj, Luke McLennan, Timothy Andeen +1
Physics-informed Neural Networks (PINNs) have been shown to be effective in solving partial differential equations by capturing the physics induced constraints as a part of the tra…
ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators
Qixing Huang, Xiangru Huang, Bo Sun +3
This paper introduces an unsupervised loss for training parametric deformation shape generators. The key idea is to enforce the preservation of local rigidity among the generated s…
Scene Synthesis via Uncertainty-Driven Attribute Synchronization
Haitao Yang, Zaiwei Zhang, Siming Yan +5
Developing deep neural networks to generate 3D scenes is a fundamental problem in neural synthesis with immediate applications in architectural CAD, computer graphics, as well as i…
Deep Predictive Learning of Carotid Stenosis Severity
Yiqun Diao, Oliver Zhao, Priya Kothapalli +2
Carotid artery stenosis is the narrowing of carotid arteries, which supplies blood to the neck and head. In this work, we train a model to predict the severity of the stenosis bloc…
Deep Contrastive Patch-Based Subspace Learning for Camera Image Signal Processing
Yunhao Yang, Yi Wang, Chandrajit Bajaj
Camera Image Signal Processing (ISP) pipelines can get appealing results in different image signal processing tasks. Nonetheless, the majority of these methods, including those emp…