51 citations · 338 across the 55 of their papers we have counts for
11 papers · 1 filter
Free-form 3D Scene Inpainting with Dual-stream GAN
Ru-Fen Jheng, Tsung-Han Wu, Jia-Fong Yeh +1
Nowadays, the need for user editing in a 3D scene has rapidly increased due to the development of AR and VR technology. However, the existing 3D scene completion task (and datasets…
Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling
Hsin-Ying Lee, Hung-Ting Su, Bing-Chen Tsai +3
While recent large-scale video-language pre-training made great progress in video question answering, the design of spatial modeling of video-language models is less fine-grained t…
Coarse-to-Fine Point Cloud Registration with SE(3)-Equivariant Representations
Cheng-Wei Lin, Tung-I Chen, Hsin-Ying Lee +2
Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose di…
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection
Ching-Yu Tseng, Yi-Rong Chen, Hsin-Ying Lee +3
To achieve accurate 3D object detection at a low cost for autonomous driving, many multi-camera methods have been proposed and solved the occlusion problem of monocular approaches.…
Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Features and NeRF-realized Mapping
Chi-Ming Chung, Yang-Che Tseng, Ya-Ching Hsu +6
A spatial AI that can perform complex tasks through visual signals and cooperate with humans is highly anticipated. To achieve this, we need a visual SLAM that easily adapts to new…
Fair Robust Active Learning by Joint Inconsistency
Tsung-Han Wu, Hung-Ting Su, Shang-Tse Chen +1
Fairness and robustness play vital roles in trustworthy machine learning. Observing safety-critical needs in various annotation-expensive vision applications, we introduce a novel…
CFVS: Coarse-to-Fine Visual Servoing for 6-DoF Object-Agnostic Peg-In-Hole Assembly
Bo-Siang Lu, Tung-I Chen, Hsin-Ying Lee +1
Robotic peg-in-hole assembly remains a challenging task due to its high accuracy demand. Previous work tends to simplify the problem by restricting the degree of freedom of the end…
GenISP: Neural ISP for Low-Light Machine Cognition
Igor Morawski, Yu-An Chen, Yu-Sheng Lin +3
Object detection in low-light conditions remains a challenging but important problem with many practical implications. Some recent works show that, in low-light conditions, object…
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
Kuan-Chih Huang, Tsung-Han Wu, Hung-Ting Su +1
Monocular 3D object detection is an important yet challenging task in autonomous driving. Some existing methods leverage depth information from an off-the-shelf depth estimator to…
D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation
Tsung-Han Wu, Yi-Syuan Liou, Shao-Ji Yuan +4
In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations. Active learning, maximizing model performance with…
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis +22
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor. Human-centered segmentation, which i…