1 code implementation • 13 Dec 2023 • Kuan-Chih Huang, Weijie Lyu, Ming-Hsuan Yang, Yi-Hsuan Tsai
Recent temporal LiDAR-based 3D object detectors achieve promising performance based on the two-stage proposal-based approach.
no code implementations • 12 Dec 2023 • Kuan-Chih Huang, Yi-Hsuan Tsai, Ming-Hsuan Yang
Finally, the training-level constraint is utilized by producing accurate and consistent 3D pseudo-labels that align with the visual data.
1 code implementation • ICCV 2023 • Kuan-Chih Huang, Ming-Hsuan Yang, Yi-Hsuan Tsai
In this paper, we find that the motion cue of objects along different time frames is critical in 3D multi-object tracking, which is less explored in existing monocular-based approaches.
1 code implementation • CVPR 2022 • Kuan-Chih Huang, Tsung-Han Wu, Hung-Ting Su, Winston H. Hsu
Moreover, different from conventional pixel-wise positional encodings, we introduce a novel depth positional encoding (DPE) to inject depth positional hints into transformers.
1 code implementation • 14 Feb 2022 • Tsung-Han Wu, Yi-Syuan Liou, Shao-Ji Yuan, Hsin-Ying Lee, Tung-I Chen, Kuan-Chih Huang, Winston H. Hsu
In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations.
no code implementations • 2 Dec 2021 • Ching-Yu Tseng, Po-Shao Lin, Yu-Jia Liou, Kuan-Chih Huang, Winston H. Hsu
Shifts Challenge: Robustness and Uncertainty under Real-World Distributional Shift is a competition held by NeurIPS 2021.
no code implementations • 22 Oct 2021 • Kuan-Chih Huang, Yu-Kai Huang, Winston H. Hsu
Vehicle velocity and inter-vehicle distance estimation are essential for ADAS (Advanced driver-assistance systems) and autonomous vehicles.
no code implementations • 4 May 2021 • Hao-Hsiang Yang, Kuan-Chih Huang, Wei-Ting Chen
The model is the encoder-decoder model with multiple adaptive feature fusion (AAF) modules.
no code implementations • 26 May 2019 • Chin-Teng Lin, Kuan-Chih Huang, Yu-Ting Liu, Yang-Yin Lin, Tsung-Yu Hsieh, Nikhil R. Pal, Shang-Lin Wu, Chieh-Ning Fang, Zehong Cao
This investigation extends that study, clarifies some issues related to our earlier work, provides the algorithm for generation of the oversamples, applies the method on several benchmark data sets, and makes application to three Brain Computer Interface (BCI) applications.