activity
20182023
most citedMove to See Better: Self-Improving Embodied Object Detection

14 citations · 28 across the 7 of their papers we have counts for

collaborators

11 papers

cs.CV2023

Analogy-Forming Transformers for Few-Shot 3D Parsing

Nikolaos Gkanatsios, Mayank Singh, Zhaoyuan Fang +2

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,…

cs.CV2022★ 4 cited

TIDEE: Tidying Up Novel Rooms using Visuo-Semantic Commonsense Priors

Gabriel Sarch, Zhaoyuan Fang, Adam W. Harley +4

We introduce TIDEE, an embodied agent that tidies up a disordered scene based on learned commonsense object placement and room arrangement priors. TIDEE explores a home environment…

cs.CV2022★ 3 cited

Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?

Adam W. Harley, Zhaoyuan Fang, Jie Li +2

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 cam…

cs.CV2022★ 6 cited

Particle Video Revisited: Tracking Through Occlusions Using Point Trajectories

Adam W. Harley, Zhaoyuan Fang, Katerina Fragkiadaki

Tracking pixels in videos is typically studied as an optical flow estimation problem, where every pixel is described with a displacement vector that locates it in the next frame. E…

cs.CV2020★ 14 cited

Move to See Better: Self-Improving Embodied Object Detection

Zhaoyuan Fang, Ayush Jain, Gabriel Sarch +2

Passive methods for object detection and segmentation treat images of the same scene as individual samples and do not exploit object permanence across multiple views. Generalizatio…

cs.CV2020

Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition

Priyanka Das, Joseph McGrath, Zhaoyuan Fang +20

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…