Search Results for author: Sangjin Lee

Found 10 papers, 3 papers with code

Multi-Scale Feature Prediction with Auxiliary-Info for Neural Image Compression

no code implementations19 Sep 2024 Chajin Shin, Sangjin Lee, Sangyoun Lee

Finally, we introduce Auxiliary info-guided Parameter Estimation (APE) module, which predicts the approximation of the latent vector and estimates the probability distribution of these residuals.

Image Compression Video Compression

STT: Stateful Tracking with Transformers for Autonomous Driving

no code implementations30 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.

Autonomous Driving

One-Shot Video Inpainting

no code implementations28 Feb 2023 Sangjin Lee, Suhwan Cho, Sangyoun Lee

Usually, a video sequence and object segmentation masks for all frames are required as the input for this task.

Object Segmentation +4

Expanded Adaptive Scaling Normalization for End to End Image Compression

1 code implementation5 Aug 2022 Chajin Shin, Hyeongmin Lee, Hanbin Son, Sangjin Lee, Dogyoon Lee, Sangyoun Lee

Then, we increase the receptive field to make the adaptive rescaling module consider the spatial correlation.

Image Compression

Exploring Discontinuity for Video Frame Interpolation

1 code implementation CVPR 2023 Sangjin Lee, Hyeongmin Lee, Chajin Shin, Hanbin Son, Sangyoun Lee

Lastly, we propose loss functions to give supervisions of the discontinuous motion areas which can be applied along with FTM and D-map.

Data Augmentation Video Frame Interpolation

Test-Time Adaptation for Out-of-distributed Image Inpainting

no code implementations2 Feb 2021 Chajin Shin, Taeoh Kim, Sangjin Lee, Sangyoun Lee

From this test-time adaptation, our network can exploit externally learned image priors from the pre-trained features as well as the internal prior of the test image explicitly.

Image Inpainting Test-time Adaptation +1

5W1H-based Expression for the Effective Sharing of Information in Digital Forensic Investigations

no code implementations26 Oct 2020 Jaehyeok Han, Jieon Kim, Sangjin Lee

Based on the 5W1H-based expression, digital information from different types of files is converted and represented in the same format of outputs.

Extrapolative-Interpolative Cycle-Consistency Learning for Video Frame Extrapolation

no code implementations27 May 2020 Sangjin Lee, Hyeongmin Lee, Taeoh Kim, Sangyoun Lee

Unlike previous studies that usually have been focused on the design of modules or construction of networks, we propose a novel Extrapolative-Interpolative Cycle (EIC) loss using pre-trained frame interpolation module to improve extrapolation performance.

Forensic analysis of the Windows telemetry for diagnostics

1 code implementation28 Feb 2020 Jaehyeok Han, Jungheum Park, Hyunji Chung, Sangjin Lee

In this paper, we introduced how to acquire RBS files telemetry and analyzed the data structure of these RBS files, which are able to determine the types of information that Windows OS have been collected.

Cryptography and Security

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