EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation 우리 연구실과 공동 연구를 진행하고 있는 서울대 윤일위 박사과정 학생이 제 1저자, 신찬용 학생이 제 2저자인 연구 결과물을 아래 링크에서 확인하실 수 있습니다. https://openaccess.thecvf.com/content/ICCV2023/papers/Yun_EGformer_Equirectangular_Geometry-biased_Transformer_for_360_Depth_Estimation_ICCV_2023_paper.pdf
논문 제목: FIACCEL: Memory Efficient Frame Interpolation Accelerator for Full-HD Video 아래 링크에서 논문을 early access 할 수 있습니다! https://ieeexplore.ieee.org/document/10306257
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!
Immersive Virtual Reality Content Supporting a Wide and Free Viewpoint Made With a Single 360° Camera https://ieeexplore.ieee.org/abstract/document/10132447
Enabling Five-Degree-of-Freedom from Low-Dimensional Light Fields with Extended Light Ray Acquisition Field-of-View https://ieeexplore.ieee.org/abstract/document/10103571
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.
Congratulations!! Our paper, “AAGAN: Accuracy-Aware Generative Adversarial Network for Supervised Tasks” is accepted at TCSVT.
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.
“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.
“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.