no code implementations • 15 Apr 2024 • Yu-Ju Tsai, Jin-Cheng Jhang, Jingjing Zheng, Wei Wang, Albert Y. C. Chen, Min Sun, Cheng-Hao Kuo, Ming-Hsuan Yang
A unique property of our Bi-Layout model is its ability to inherently detect ambiguous regions by comparing the two predictions.
no code implementations • 3 Apr 2024 • Jing Liang, Zhuo Deng, Zheming Zhou, Omid Ghasemalizadeh, Dinesh Manocha, Min Sun, Cheng-Hao Kuo, Arnie Sen
We present a novel end-to-end algorithm (PoCo) for the indoor RGB-D place recognition task, aimed at identifying the most likely match for a given query frame within a reference database.
no code implementations • 29 Mar 2024 • Yun-Yun Tsai, Fu-Chen Chen, Albert Y. C. Chen, Junfeng Yang, Che-Chun Su, Min Sun, Cheng-Hao Kuo
For vision tasks, recent studies have shown that test-time adaptation employing diffusion models can achieve state-of-the-art accuracy improvements on OOD samples by generating new samples that align with the model's domain without the need to modify the model's weights.
no code implementations • 15 Oct 2023 • Xiaotong Chen, Zheming Zhou, Zhuo Deng, Omid Ghasemalizadeh, Min Sun, Cheng-Hao Kuo, Arnie Sen
Reconstructing transparent objects using affordable RGB-D cameras is a persistent challenge in robotic perception due to inconsistent appearances across views in the RGB domain and inaccurate depth readings in each single-view.
no code implementations • ICCV 2023 • Tao Tu, Shun-Po Chuang, Yu-Lun Liu, Cheng Sun, Ke Zhang, Donna Roy, Cheng-Hao Kuo, Min Sun
The results demonstrate that ImGeoNet outperforms the current state-of-the-art multi-view image-based method, ImVoxelNet, on all three datasets in terms of detection accuracy.
Ranked #24 on 3D Object Detection on ScanNetV2
1 code implementation • 4 Aug 2023 • Xuefeng Hu, Ke Zhang, Lu Xia, Albert Chen, Jiajia Luo, Yuyin Sun, Ken Wang, Nan Qiao, Xiao Zeng, Min Sun, Cheng-Hao Kuo, Ram Nevatia
Large-scale Pre-Training Vision-Language Model such as CLIP has demonstrated outstanding performance in zero-shot classification, e. g. achieving 76. 3% top-1 accuracy on ImageNet without seeing any example, which leads to potential benefits to many tasks that have no labeled data.
1 code implementation • ICCV 2023 • Liqiang He, Wei Wang, Albert Chen, Min Sun, Cheng-Hao Kuo, Sinisa Todorovic
We propose a Bidirectional Alignment for domain adaptive Detection with Transformers (BiADT) to improve cross domain object detection performance.
1 code implementation • 22 Dec 2022 • Evin Pınar Örnek, Aravindhan K Krishnan, Shreekant Gayaka, Cheng-Hao Kuo, Arnie Sen, Nassir Navab, Federico Tombari
We introduce a zero-shot split for Tabletop Objects Dataset (TOD-Z) to enable this study and present a method that uses annotated objects to learn the ``objectness'' of pixels and generalize to unseen object categories in cluttered indoor environments.
no code implementations • 30 Jul 2022 • Shao-Yuan Lo, Wei Wang, Jim Thomas, Jingjing Zheng, Vishal M. Patel, Cheng-Hao Kuo
In this paper, we propose a novel UDA method for MDE, referred to as Learning Feature Decomposition for Adaptation (LFDA), which learns to decompose the feature space into content and style components.
no code implementations • 5 Apr 2021 • Haoqi Li, Yelin Kim, Cheng-Hao Kuo, Shrikanth Narayanan
Key challenges in developing generalized automatic emotion recognition systems include scarcity of labeled data and lack of gold-standard references.
1 code implementation • CVPR 2020 • Chenyan Wu, Yukun Chen, Jiajia Luo, Che-Chun Su, Anuja Dawane, Bikramjot Hanzra, Zhuo Deng, Bilan Liu, James Wang, Cheng-Hao Kuo
We present COCO-MEBOW (Monocular Estimation of Body Orientation in the Wild), a new large-scale dataset for orientation estimation from a single in-the-wild image.