[Paper]

2023.8 Interactive video 를 가능하게 하는 360도 영상의 depth estimation 논문이 IEEE Transactions on Multimedia에 accept 되었습니다.

Interactive video 를 가능하게 하는 360도 영상의 depth estimation 논문이 IEEE Transactions on Multimedia에 accept 되었습니다. “Adversarial Mixture Density Network and Uncertainty-based Joint Learning for 360 Monocular Depth Estimation” 출판되면 소식 업데이트 하겠습니다!

2023.2 Our paper is accepted at ISCAS’23

서용욱/류광철 학생의 논문 “Improving the Compression Efficiency of Displacement Using Morton-Ordered Micro-Image in Video-Based Dynamic Mesh Coding” 이 2023년도 5월에 개최 예정인 IEEE International Symposium on Circuits and Systems (ISCAS) 에 accept 되었습니다.

Our paper is accepted at CVPR 2022.

Congratulations!! Our paper, “Beyond Semantic to Instance Segmentation: Weakly-Supervised Instance Segmentation via Semantic Knowledge Transfer and Self-Refinement ” is accepted at CVPR 2022.This work is the result of joint research with NAVER CLOVA.

Our paper, is accepted at AAAI2022.

“Improving 360-degree Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning ”, Congratulations!! Our paper, “Improving 360-degree Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning ”, is accepted at AAAI 2022.

Our paper, is accepted at IEEE TCSVT.

“Data Orchestration for Accelerating GPU-based Light Field Rendering Aiming at a Wide Virtual Space”, Congratulations!! Our paper, “Data Orchestration for Accelerating GPU-based Light Field Rendering Aiming at a Wide Virtual Space”, is accepted at IEEE Transactions on Circuits and Systems for Video Technology. The first author is Seungho Lee.

Our paper, is published at MDPI Sensors

“Improved Light Field Compression Efficiency through BM3D-Based Denoising using Inter-View Correlation”, [Paper]Our paper, “Improved Light Field Compression Efficiency through BM3D-Based Denoising using Inter-View Correlation”, is published at MDPI Sensors. Please see https://www.mdpi.com/1424-8220/21/9/2919

Our paper, is accepted at IEEE Transactions

“A Lightweight and Efficient GPU for Near Data Processing Utilizing Data Access Pattern of Image Processing”, on Computers [Paper] Our paper, “A Lightweight and Efficient GPU for Near Data Processing Utilizing Data Access Pattern of Image Processing”, is accepted at IEEE Transactions on Computers.  Please see https://ieeexplore.ieee.org/abstract/document/9047953