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08/28/2023
Flexible Techniques for Differentiable Rendering with 3D Gaussians
Fast, reliable shape reconstruction is an essential ingredient in many c...
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08/08/2023
Optimizing Algorithms From Pairwise User Preferences
Typical black-box optimization approaches in robotics focus on learning ...
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06/24/2023
Thinking Like an Annotator: Generation of Dataset Labeling Instructions
Large-scale datasets are essential to modern day deep learning. Advocate...
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03/27/2023
Object Discovery from Motion-Guided Tokens
Object discovery – separating objects from the background without manual...
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03/13/2023
Discovering Multiple Algorithm Configurations
Many practitioners in robotics regularly depend on classic, hand-designe...
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11/21/2022
Deep Projective Rotation Estimation through Relative Supervision
Orientation estimation is the core to a variety of vision and robotics t...
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08/25/2022
Learning Continuous Implicit Representation for Near-Periodic Patterns
Near-Periodic Patterns (NPP) are ubiquitous in man-made scenes and are c...
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07/21/2022
Approximate Differentiable Rendering with Algebraic Surfaces
Differentiable renderers provide a direct mathematical link between an o...
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06/09/2022
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields
Comprehensive 3D scene understanding, both geometrically and semanticall...
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05/26/2022
Semantically Supervised Appearance Decomposition for Virtual Staging from a Single Panorama
We describe a novel approach to decompose a single panorama of an empty ...
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03/18/2022
Discovering Objects that Can Move
This paper studies the problem of object discovery – separating objects ...
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06/25/2021
Generative Modeling for Multi-task Visual Learning
Generative modeling has recently shown great promise in computer vision,...
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06/20/2021
Learning to Track Object Position through Occlusion
Occlusion is one of the most significant challenges encountered by objec...
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04/28/2021
ZePHyR: Zero-shot Pose Hypothesis Rating
Pose estimation is a basic module in many robot manipulation pipelines. ...
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12/17/2020
PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
Visual data in autonomous driving perception, such as camera image and L...
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10/15/2020
Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method
This paper studies the safe reinforcement learning (RL) problem without ...
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08/22/2020
Few-Shot Learning with Intra-Class Knowledge Transfer
We consider the few-shot classification task with an unbalanced dataset,...
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08/17/2020
Alpha Net: Adaptation with Composition in Classifier Space
Deep learning classification models typically train poorly on classes wi...
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08/16/2020
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Generative modeling has recently shown great promise in computer vision,...
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08/01/2020
PanoNet: Real-time Panoptic Segmentation through Position-Sensitive Feature Embedding
We propose a simple, fast, and flexible framework to generate simultaneo...
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07/30/2020
MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments
Multi-agent navigation in dynamic environments is of great industrial va...
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07/02/2020
Learning Orientation Distributions for Object Pose Estimation
For robots to operate robustly in the real world, they should be aware o...
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06/28/2020
Unsupervised Learning of Video Representations via Dense Trajectory Clustering
This paper addresses the task of unsupervised learning of representation...
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11/29/2019
Learning Generalizable Representations via Diverse Supervision
The problem of rare category recognition has received a lot of attention...
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10/15/2019
Explainable Semantic Mapping for First Responders
One of the key challenges in the semantic mapping problem in postdisaste...
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07/27/2019
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions
Semantic segmentation with Convolutional Neural Networks is a memory-int...
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07/18/2019
Growing a Brain: Fine-Tuning by Increasing Model Capacity
CNNs have made an undeniable impact on computer vision through the abili...
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06/11/2019
Edge-Direct Visual Odometry
In this paper we propose an edge-direct visual odometry algorithm that e...
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05/28/2019
Image Deformation Meta-Networks for One-Shot Learning
Humans can robustly learn novel visual concepts even when images undergo...
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05/07/2019
Learning Unsupervised Multi-View Stereopsis via Robust Photometric Consistency
We present a learning based approach for multi-view stereopsis (MVS). Wh...
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04/29/2019
A Study on Action Detection in the Wild
The recent introduction of the AVA dataset for action detection has caus...
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04/11/2019
Direct Fitting of Gaussian Mixture Models
When fitting Gaussian Mixture Models to 3D geometry, the model is typica...
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12/21/2018
Learning Compositional Representations for Few-Shot Recognition
One of the key limitations of modern deep learning based approaches lies...
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12/09/2018
A Structured Model For Action Detection
A dominant paradigm for learning-based approaches in computer vision is ...
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11/27/2018
Iterative Transformer Network for 3D Point Cloud
3D point cloud is an efficient and flexible representation of 3D structu...
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11/08/2018
Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels
Training deep networks for semantic segmentation requires annotation of ...
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08/02/2018
PCN: Point Completion Network
Shape completion, the problem of estimating the complete geometry of obj...
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01/16/2018
Low-Shot Learning from Imaginary Data
Humans can quickly learn new visual concepts, perhaps because they can e...
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12/04/2017
Learning by Asking Questions
We introduce an interactive learning framework for the development and t...
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10/30/2017
Log-DenseNet: How to Sparsify a DenseNet
Skip connections are increasingly utilized by deep neural networks to im...
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09/25/2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks
Recurrent neural networks (RNNs) are a vital modeling technique that rel...
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08/22/2017
Anytime Neural Network: a Versatile Trade-off Between Computation and Accuracy
Anytime predictors first produce crude results quickly, and then continu...
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08/04/2017
Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
A major impediment in rapidly deploying object detection models for inst...
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12/08/2016
Contextual Visual Similarity
Measuring visual similarity is critical for image understanding. But wha...
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12/04/2016
General models for rational cameras and the case of two-slit projections
The rational camera model recently introduced in [19] provides a general...
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09/28/2016
A Discriminative Framework for Anomaly Detection in Large Videos
We address an anomaly detection setting in which training sequences are ...
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08/01/2016
Learning Transferable Policies for Monocular Reactive MAV Control
The ability to transfer knowledge gained in previous tasks into new cont...
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07/28/2016
Introspective Perception: Learning to Predict Failures in Vision Systems
As robots aspire for long-term autonomous operations in complex dynamic ...
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06/25/2016
An Uncertain Future: Forecasting from Static Images using Variational Autoencoders
In a given scene, humans can often easily predict a set of immediate fut...
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04/12/2016
