no code implementations • 11 Mar 2024 • Rukhshanda Hussain, Hui Xian Grace Lim, BorChun Chen, Mubarak Shah, Ser Nam Lim
Second, we establish that the concept of a view can be disentangled and transferred to a novel object irrespective of the original object's identify from which the views are learnt.
no code implementations • 15 Mar 2022 • A. Tuan Nguyen, Ser Nam Lim, Philip Torr
To tackle this problem, a great amount of research has been done to study the training procedure of a network to improve its robustness.
no code implementations • NeurIPS 2021 • Keyu Tian, Chen Lin, Ser Nam Lim, Wanli Ouyang, Puneet Dokania, Philip Torr
Automated data augmentation (ADA) techniques have played an important role in boosting the performance of deep models.
1 code implementation • 24 Nov 2018 • Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser Nam Lim, Larry S. Davis
The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.
no code implementations • ECCV 2018 • Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gkhan Uzunbas, Tom Goldstein, Ser Nam Lim, Larry S. Davis
In particular, given an image from the source domain and unlabeled samples from the target domain, the generator synthesizes new images on-the-fly to resemble samples from the target domain in appearance and the segmentation network further refines high-level features before predicting semantic maps, both of which leverage feature statistics of sampled images from the target domain.
no code implementations • CVPR 2018 • Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa
In this work, we focus on adapting the representations learned by segmentation networks across synthetic and real domains.
no code implementations • The IEEE International Conference on Computer Vision (ICCV), 2017 2017 • Wenbo Li, Longyin Wen, Ming-Ching Chang, Ser Nam Lim, Siwei Lyu
The RNNs in RNN-T are co-trained with the action category hierarchy, which determines the structure of RNN-T.
Ranked #107 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • ICCV 2017 • Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim
Convolutional Neural Networks have been a subject of great importance over the past decade and great strides have been made in their utility for producing state of the art performance in many computer vision problems.
no code implementations • 22 May 2017 • Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser Nam Lim
In this paper, we present an efficient approach to perform adversarial training by perturbing intermediate layer activations and study the use of such perturbations as a regularizer during training.
no code implementations • 23 Mar 2017 • Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim
Convolutional Neural Networks have been a subject of great importance over the past decade and great strides have been made in their utility for producing state of the art performance in many computer vision problems.
no code implementations • CVPR 2017 • Mustafa Devrim Kaba, Mustafa Gokhan Uzunbas, Ser Nam Lim
We present a Reinforcement Learning (RL) solution to the view planning problem (VPP), which generates a sequence of view points that are capable of sensing all accessible area of a given object represented as a 3D model.