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David Han

7 accepted papers

2026

LRDDv3: High-Resolution Long-Range Drone Detection Dataset with Range Information and Thermal Data

Knut Peterson, Zaid Mayers, Md Azmain Yousuf, Priontu Chowdhury, Solmaz Arezoomandan, Asher Julius Zaczepinski +2
ICRA 2026poster

Unmanned Aerial Vehicles (UAVs) have quickly become common in various airspaces, representing a wide range of applications from recreation flying to commercial photography and package delivery. With the increasing prevalence of UAVs, it becomes critical that both manned and unmanned aircraft can det…

Cited by 0Source ↗PDF ↗Scholar ↗
2022

Injecting 3D Perception of Controllable NeRF-GAN into StyleGAN for Editable Portrait Image Synthesis

Jeong-gi Kwak, Yuanming Li, Dongsik Yoon, Donghyeon Kim, David Han, Hanseok Ko
ECCV 2022poster

"Over the years, 2D GANs have achieved great successes in photorealistic portrait generation. However, they lack 3D understanding in the generation process, thus they suffer from multi-view inconsistency problem. To alleviate the issue, many 3D-aware GANs have been proposed and shown notable results…

Cited by 29Source ↗PDF ↗code ↗Scholar ↗
2021

Consolidating Kinematic Models to Promote Coordinated Mobile Manipulations

Ziyuan Jiao, Zeyu Zhang, Xin Jiang, David Han, Song-Chun Zhu, Yixin Zhu +1
IROS 2021poster

We construct a Virtual Kinematic Chain (VKC) that readily consolidates the kinematics of the mobile base, the arm, and the object to be manipulated in mobile manipulations. Accordingly, a mobile manipulation task is represented by altering the state of the constructed VKC, which can be converted to…

Cited by 21Source ↗code ↗Scholar ↗
2021

Efficient Task Planning for Mobile Manipulation: a Virtual Kinematic Chain Perspective

Ziyuan Jiao, Zeyu Zhang, Weiqi Wang, David Han, Song-Chun Zhu, Yixin Zhu +1
IROS 2021poster

We present a Virtual Kinematic Chain (VKC) perspective, a simple yet effective method, to improve task planning efficacy for mobile manipulation. By consolidating the kinematics of the mobile base, the arm, and the object being manipulated collectively as a whole, this novel VKC perspective naturall…

Cited by 21Source ↗code ↗Scholar ↗
2021

Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments

Youngsaeng Jin, David Han, Hanseok Ko
IROS 2021poster

With the availability of many datasets tailored for autonomous driving in real-world urban scenes, semantic segmentation for urban driving scenes achieves significant progress. However, semantic segmentation for off-road, unstructured environments is not widely studied. Directly applying existing se…

Cited by 16Source ↗Scholar ↗
2020

Learning Object Placement by Inpainting for Compositional Data Augmentation

Lingzhi Zhang, Tarmily Wen, Jie Min, Jiancong Wang, David Han, Jianbo Shi
ECCV 2020poster

We study the problem of common sense placement of visual objects in an image.  This involves multiple aspects of visual recognition: the instance segmentation of the scene, 3D layout, and common knowledge of how objects are placed and where objects are moving in the 3D scene. This seemingly simple t…

Cited by 78Source ↗PDF ↗Scholar ↗
2019

A RUGD Dataset for Autonomous Navigation and Visual Perception in Unstructured Outdoor Environments

Maggie Wigness, Sungmin Eum, John G. Rogers, David Han, Heesung Kwon
IROS 2019poster

Research in autonomous driving has benefited from a number of visual datasets collected from mobile platforms, leading to improved visual perception, greater scene understanding, and ultimately higher intelligence. However, this set of existing data collectively represents only highly structured, ur…

Cited by 208Source ↗Scholar ↗