Search Results for author:
Found 12 papers, 7 papers with code
GSIR: Generalizable 3D Shape Interpretation and Reconstruction
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.
Analogy-Forming Transformers for Few-Shot 3D Parsing
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.
TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors
We introduce TIDEE, an embodied agent that tidies up a disordered scene based on learned commonsense object placement and room arrangement priors.
Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?
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
Particle Video Revisited: Tracking Through Occlusions Using Point Trajectories
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.
Move to See Better: Self-Improving Embodied Object Detection
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.
Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition
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).
Open Source Iris Recognition Hardware and Software with Presentation Attack Detection
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.
Iris Presentation Attack Detection: Where Are We Now?
As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount.
Robust Iris Presentation Attack Detection Fusing 2D and 3D Information
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.
AlignNet: A Unifying Approach to Audio-Visual Alignment
We present AlignNet, a model that synchronizes videos with reference audios under non-uniform and irregular misalignments.
Iris Presentation Attack Detection Based on Photometric Stereo Features
2, 900 iris image pairs acquired from approx.
Binary Classification
Cross-Domain Iris Presentation Attack Detection
