no code implementations • 30 Apr 2024 • Longlong Jing, Ruichi Yu, Xu Chen, Zhengli Zhao, Shiwei Sheng, Colin Graber, Qi Chen, Qinru Li, Shangxuan Wu, Han Deng, Sangjin Lee, Chris Sweeney, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, Zijian Guo, Yin Zhou, Mingxing Tan, Weilong Yang, CongCong Li
In this paper, we propose STT, a Stateful Tracking model built with Transformers, that can consistently track objects in the scenes while also predicting their states accurately.
no code implementations • 4 Jan 2024 • Zihao Xiao, Longlong Jing, Shangxuan Wu, Alex Zihao Zhu, Jingwei Ji, Chiyu Max Jiang, Wei-Chih Hung, Thomas Funkhouser, Weicheng Kuo, Anelia Angelova, Yin Zhou, Shiwei Sheng
3D panoptic segmentation is a challenging perception task, especially in autonomous driving.
1 code implementation • CVPR 2023 • Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani
Automatically estimating 3D skeleton, shape, camera viewpoints, and part articulation from sparse in-the-wild image ensembles is a severely under-constrained and challenging problem.
no code implementations • 11 Aug 2022 • Xianzhi Du, Wei-Chih Hung, Tsung-Yi Lin
This paper summarizes model improvements and inference-time optimizations for the popular anchor-based detectors in the scenes of autonomous driving.
no code implementations • 7 Jul 2022 • Chun-Han Yao, Wei-Chih Hung, Yuanzhen Li, Michael Rubinstein, Ming-Hsuan Yang, Varun Jampani
In this work, we propose a practical problem setting to estimate 3D pose and shape of animals given only a few (10-30) in-the-wild images of a particular animal species (say, horse).
1 code implementation • 15 Jun 2022 • Wei-Chih Hung, Vincent Casser, Henrik Kretzschmar, Jyh-Jing Hwang, Dragomir Anguelov
However, camera-only detectors have limited depth accuracy, which may cause otherwise reasonable predictions that suffer from such longitudinal localization errors to be treated as false positives.
no code implementations • 14 Oct 2021 • Yufeng Wang, Yi-Hsuan Tsai, Wei-Chih Hung, Wenrui Ding, Shuo Liu, Ming-Hsuan Yang
Multi-Task Learning (MTL) aims to enhance the model generalization by sharing representations between related tasks for better performance.
no code implementations • ICCV 2021 • Chun-Han Yao, Wei-Chih Hung, Varun Jampani, Ming-Hsuan Yang
Reasoning 3D shapes from 2D images is an essential yet challenging task, especially when only single-view images are at our disposal.
1 code implementation • 30 Jun 2021 • Xianzhi Du, Barret Zoph, Wei-Chih Hung, Tsung-Yi Lin
We benchmark these improvements on the vanilla ResNet-FPN backbone with RetinaNet and RCNN detectors.
Ranked #57 on Object Detection on COCO minival
no code implementations • ICLR 2022 • Tsai-Shien Chen, Wei-Chih Hung, Hung-Yu Tseng, Shao-Yi Chien, Ming-Hsuan Yang
Self-supervised learning has recently shown great potential in vision tasks through contrastive learning, which aims to discriminate each image, or instance, in the dataset.
no code implementations • 18 Aug 2020 • Wei-Chih Hung, Henrik Kretzschmar, Tsung-Yi Lin, Yuning Chai, Ruichi Yu, Ming-Hsuan Yang, Dragomir Anguelov
Robust multi-object tracking (MOT) is a prerequisite fora safe deployment of self-driving cars.
1 code implementation • 12 Aug 2020 • Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai, Yu-Ting Chang, Yijun Li, Deng Cai, Ming-Hsuan Yang
Caricature is an artistic drawing created to abstract or exaggerate facial features of a person.
no code implementations • 3 Aug 2020 • Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang
Obtaining object response maps is one important step to achieve weakly-supervised semantic segmentation using image-level labels.
1 code implementation • CVPR 2020 • Yu-Ting Chang, Qiaosong Wang, Wei-Chih Hung, Robinson Piramuthu, Yi-Hsuan Tsai, Ming-Hsuan Yang
Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions.
1 code implementation • CVPR 2020 • K L Navaneet, Ansu Mathew, Shashank Kashyap, Wei-Chih Hung, Varun Jampani, R. Venkatesh Babu
We learn both 3D point cloud reconstruction and pose estimation networks in a self-supervised manner, making use of differentiable point cloud renderer to train with 2D supervision.
3D Object Reconstruction From A Single Image 3D Point Cloud Reconstruction +2
1 code implementation • 24 Oct 2019 • Han-Kai Hsu, Chun-Han Yao, Yi-Hsuan Tsai, Wei-Chih Hung, Hung-Yu Tseng, Maneesh Singh, Ming-Hsuan Yang
This intermediate domain is constructed by translating the source images to mimic the ones in the target domain.
1 code implementation • 13 May 2019 • Wenqing Chu, Wei-Chih Hung, Yi-Hsuan Tsai, Deng Cai, Ming-Hsuan Yang
However, current state-of-the-art face parsing methods require large amounts of labeled data on the pixel-level and such process for caricature is tedious and labor-intensive.
1 code implementation • CVPR 2019 • Wei-Chih Hung, Varun Jampani, Sifei Liu, Pavlo Molchanov, Ming-Hsuan Yang, Jan Kautz
Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations.
Ranked #4 on Unsupervised Keypoint Estimation on CUB
1 code implementation • ECCV 2018 • Wei-Chih Hung, Jianming Zhang, Xiaohui Shen, Zhe Lin, Joon-Young Lee, Ming-Hsuan Yang
Specifically, given a foreground image and a background image, our proposed method automatically generates a set of blending photos with scores that indicate the aesthetics quality with the proposed quality network and policy network.
12 code implementations • CVPR 2018 • Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, Manmohan Chandraker
In this paper, we propose an adversarial learning method for domain adaptation in the context of semantic segmentation.
Ranked #3 on Domain Adaptation on Synscapes-to-Cityscapes
13 code implementations • ICLR 2018 • Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, Ming-Hsuan Yang
We propose a method for semi-supervised semantic segmentation using an adversarial network.
1 code implementation • ICCV 2017 • Wei-Chih Hung, Yi-Hsuan Tsai, Xiaohui Shen, Zhe Lin, Kalyan Sunkavalli, Xin Lu, Ming-Hsuan Yang
We present a scene parsing method that utilizes global context information based on both the parametric and non- parametric models.
no code implementations • 14 Sep 2017 • Jingchun Cheng, Sifei Liu, Yi-Hsuan Tsai, Wei-Chih Hung, Shalini De Mello, Jinwei Gu, Jan Kautz, Shengjin Wang, Ming-Hsuan Yang
In addition, we apply a filter on the refined score map that aims to recognize the best connected region using spatial and temporal consistencies in the video.