no code implementations • ECCV 2020 • Jianren Wang, Zhaoyuan Fang
Single image 3D shape interpretation and reconstruction are closely related to each other but have long been studied separately and often end up with priors that are highly biased by training classes.
no code implementations • 27 Apr 2023 • Nikolaos Gkanatsios, Mayank Singh, Zhaoyuan Fang, Shubham Tulsiani, Katerina Fragkiadaki
We present Analogical Networks, a model that encodes domain knowledge explicitly, in a collection of structured labelled 3D scenes, in addition to implicitly, as model parameters, and segments 3D object scenes with analogical reasoning: instead of mapping a scene to part segments directly, our model first retrieves related scenes from memory and their corresponding part structures, and then predicts analogous part structures for the input scene, via an end-to-end learnable modulation mechanism.
1 code implementation • 21 Jul 2022 • Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley, Paul Schydlo, Michael J. Tarr, Saurabh Gupta, Katerina Fragkiadaki
We introduce TIDEE, an embodied agent that tidies up a disordered scene based on learned commonsense object placement and room arrangement priors.
1 code implementation • 16 Jun 2022 • Adam W. Harley, Zhaoyuan Fang, Jie Li, Rares Ambrus, Katerina Fragkiadaki
Building 3D perception systems for autonomous vehicles that do not rely on high-density LiDAR is a critical research problem because of the expense of LiDAR systems compared to cameras and other sensors.
Autonomous Vehicles Bird's-Eye View Semantic Segmentation +1
1 code implementation • 8 Apr 2022 • Adam W. Harley, Zhaoyuan Fang, Katerina Fragkiadaki
In this paper, we revisit Sand and Teller's "particle video" approach, and study pixel tracking as a long-range motion estimation problem, where every pixel is described with a trajectory that locates it in multiple future frames.
1 code implementation • 30 Nov 2020 • Zhaoyuan Fang, Ayush Jain, Gabriel Sarch, Adam W. Harley, Katerina Fragkiadaki
Experiments on both indoor and outdoor datasets show that (1) our method obtains high-quality 2D and 3D pseudo-labels from multi-view RGB-D data; (2) fine-tuning with these pseudo-labels improves the 2D detector significantly in the test environment; (3) training a 3D detector with our pseudo-labels outperforms a prior self-supervised method by a large margin; (4) given weak supervision, our method can generate better pseudo-labels for novel objects.
no code implementations • 1 Sep 2020 • Priyanka Das, Joseph McGrath, Zhaoyuan Fang, Aidan Boyd, Ganghee Jang, Amir Mohammadi, Sandip Purnapatra, David Yambay, Sébastien Marcel, Mateusz Trokielewicz, Piotr Maciejewicz, Kevin Bowyer, Adam Czajka, Stephanie Schuckers, Juan Tapia, Sebastian Gonzalez, Meiling Fang, Naser Damer, Fadi Boutros, Arjan Kuijper, Renu Sharma, Cunjian Chen, Arun Ross
Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD).
2 code implementations • 19 Aug 2020 • Zhaoyuan Fang, Adam Czajka
This paper proposes the first known to us open source hardware and software iris recognition system with presentation attack detection (PAD), which can be easily assembled for about 75 USD using Raspberry Pi board and a few peripherals.
no code implementations • 23 Jun 2020 • Aidan Boyd, Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount.
no code implementations • 21 Feb 2020 • Zhaoyuan Fang, Adam Czajka, Kevin W. Bowyer
Diversity and unpredictability of artifacts potentially presented to an iris sensor calls for presentation attack detection methods that are agnostic to specificity of presentation attack instruments.
1 code implementation • 12 Feb 2020 • Jianren Wang, Zhaoyuan Fang, Hang Zhao
We present AlignNet, a model that synchronizes videos with reference audios under non-uniform and irregular misalignments.
2 code implementations • 18 Nov 2018 • Adam Czajka, Zhaoyuan Fang, Kevin W. Bowyer
2, 900 iris image pairs acquired from approx.
Binary Classification Cross-Domain Iris Presentation Attack Detection