10.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS1.5k papers
- Michigan State UniversityUS1.5k papers
- Centre National de la Recherche ScientifiqueFR1.4k papers
- Lawrence Berkeley National LaboratoryUS1.4k papers
- McGill UniversityCA1.4k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR1.3k papers
- University of ManchesterGB1.3k papers
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- University of TorontoCA1.3k papers
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19 papers · 2 filters
Signed Input Regularization
Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh
Over-parameterized deep models usually over-fit to a given training distribution, which makes them sensitive to small changes and out-of-distribution samples at inference time, lea…
Sim2Real Predictivity: Does Evaluation in Simulation Predict Real-World Performance?
Abhishek Kadian, Joanne Truong, Aaron Gokaslan +6
Does progress in simulation translate to progress on robots? If one method outperforms another in simulation, how likely is that trend to hold in reality on a robot? We examine thi…
Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference
Nelson Nauata, Yasutaka Furukawa
This paper tackles a 2D architecture vectorization problem, whose task is to infer an outdoor building architecture as a 2D planar graph from a single RGB image. We provide a new b…
Generating Videos of Zero-Shot Compositions of Actions and Objects
Megha Nawhal, Mengyao Zhai, Andreas Lehrmann +2
Human activity videos involve rich, varied interactions between people and objects. In this paper we develop methods for generating such videos -- making progress toward addressing…
Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction
Fuyang Zhang, Nelson Nauata, Yasutaka Furukawa
This paper proposes a novel message passing neural (MPN) architecture Conv-MPN, which reconstructs an outdoor building as a planar graph from a single RGB image. Conv-MPN is specif…
Leveraging Multi-view Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation
Renjiao Yi, Ping Tan, Stephen Lin
We present an unsupervised approach for factorizing object appearance into highlight, shading, and albedo layers, trained by multi-view real images. To do so, we construct a multi-…
PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes
Rundi Wu, Yixin Zhuang, Kai Xu +2
We introduce PQ-NET, a deep neural network which represents and generates 3D shapes via sequential part assembly. The input to our network is a 3D shape segmented into parts, where…
BSP-Net: Generating Compact Meshes via Binary Space Partitioning
Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang
Polygonal meshes are ubiquitous in the digital 3D domain, yet they have only played a minor role in the deep learning revolution. Leading methods for learning generative models of…
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
Erik Wijmans, Abhishek Kadian, Ari Morcos +5
We present Decentralized Distributed Proximal Policy Optimization (DD-PPO), a method for distributed reinforcement learning in resource-intensive simulated environments. DD-PPO is…
Using an AI creativity system to explore how aesthetic experiences are processed along the brains perceptual neural pathways
Vanessa Utz, Steve DiPaola
With the increased sophistication of AI techniques, the application of these systems has been expanding to ever newer fields. Increasingly, these systems are being used in modeling…
Learning Guided Convolutional Network for Depth Completion
Jie Tang, Fei-Peng Tian, Wei Feng +2
Dense depth perception is critical for autonomous driving and other robotics applications. However, modern LiDAR sensors only provide sparse depth measurement. It is thus necessary…
LayoutVAE: Stochastic Scene Layout Generation From a Label Set
Akash Abdu Jyothi, Thibaut Durand, Jiawei He +2
Recently there is an increasing interest in scene generation within the research community. However, models used for generating scene layouts from textual description largely ignor…
Datasets for Face and Object Detection in Fisheye Images
Jianglin Fu, Ivan V. Bajic, Rodney G. Vaughan
We present two new fisheye image datasets for training face and object detection models: VOC-360 and Wider-360. The fisheye images are created by post-processing regular images col…
Visual Diagnosis of Dermatological Disorders: Human and Machine Performance
Jeremy Kawahara, Ghassan Hamarneh
Skin conditions are a global health concern, ranking the fourth highest cause of nonfatal disease burden when measured as years lost due to disability. As diagnosing, or classifyin…
AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri +3
We introduce AdaCoSeg, a deep neural network architecture for adaptive co-segmentation of a set of 3D shapes represented as point clouds. Differently from the familiar single-insta…
LOGAN: Unpaired Shape Transform in Latent Overcomplete Space
Kangxue Yin, Zhiqin Chen, Hui Huang +2
We introduce LOGAN, a deep neural network aimed at learning general-purpose shape transforms from unpaired domains. The network is trained on two sets of shapes, e.g., tables and c…
PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
Fenggen Yu, Kun Liu, Yan Zhang +2
Deep learning approaches to 3D shape segmentation are typically formulated as a multi-class labeling problem. Existing models are trained for a fixed set of labels, which greatly l…
On instabilities of deep learning in image reconstruction - Does AI come at a cost?
Vegard Antun, Francesco Renna, Clarice Poon +2
Deep learning, due to its unprecedented success in tasks such as image classification, has emerged as a new tool in image reconstruction with potential to change the field. In this…
FDDB-360: Face Detection in 360-degree Fisheye Images
Jianglin Fu, Saeed Ranjbar Alvar, Ivan V. Bajic +1
360-degree cameras offer the possibility to cover a large area, for example an entire room, without using multiple distributed vision sensors. However, geometric distortions introd…