81 to 90 of 227 Results
Sep 25, 2024 - S-Lab for Advanced Intelligence
Xu, Baixin; Hu, Jiangbei; Hou, Fei; Lin, Kwan-Yee; Wu, Wayne; Qian, Chen; He, Ying, 2024, "Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering", https://doi.org/10.21979/N9/0C9BU9, DR-NTU (Data), V1
The advancements in neural rendering have increased the need for techniques that enable intuitive editing of 3D objects represented as neural implicit surfaces. This paper introduces a novel neural algorithm for parameterizing neural implicit surfaces to simple parametric domains... |
Sep 25, 2024 - S-Lab for Advanced Intelligence
Xu, Qianxiong; Lin, Guosheng; Loy, Chen Change; Long, Cheng; Li, Ziyue; Zhao, Rui, 2024, "Eliminating Feature Ambiguity for Few-Shot Segmentation", https://doi.org/10.21979/N9/CIOE8Y, DR-NTU (Data), V1
Recent advancements in few-shot segmentation (FSS) have exploited pixel-by-pixel matching between query and support features, typically based on cross attention, which selectively activate query foreground (FG) features that correspond to the same-class support FG features. Howev... |
Sep 25, 2024 - S-Lab for Advanced Intelligence
Feng, Ruicheng; Li, Chongyi; Loy, Chen Change, 2024, "Kalman-Inspired Feature Propagation for Video Face Super-Resolution", https://doi.org/10.21979/N9/FMVNYY, DR-NTU (Data), V1
Despite the promising progress of face image super-resolution, video face super-resolution remains relatively under-explored. Existing approaches either adapt general video super-resolution networks to face datasets or apply established face image super-resolution models independ... |
Sep 20, 2024 - S-Lab for Advanced Intelligence
Hu, Tao; Hong, Fangzhou; Liu, Ziwei, 2024, "StructLDM: Structured Latent Diffusion for 3D Human Generation", https://doi.org/10.21979/N9/BXUEXV, DR-NTU (Data), V1
Recent 3D human generative models have achieved remarkable progress by learning 3D-aware GANs from 2D images. However, existing 3D human generative methods model humans in a compact 1D latent space, ignoring the articulated structure and semantics of human body topology. In this... |
Loy, Chen Change, 2024, "EdgeSAM", https://doi.org/10.21979/N9/KF8798, DR-NTU (Data), V2
We present EdgeSAM, an accelerated variant of the Segment Anything Model (SAM), optimized for efficient execution on edge devices with minimal compromise in performance. Our approach involves distilling the original ViT-based SAM image encoder into a purely CNN-based architecture... |
Loy, Chen Change, 2024, "CodeFormer", https://doi.org/10.21979/N9/X3IBKH, DR-NTU (Data), V4
Blind face restoration is a highly ill-posed problem that often requires auxiliary guidance to 1) improve the mapping from degraded inputs to desired outputs, or 2) complement high-quality details lost in the inputs. In this paper, we demonstrate that the learned discrete codeboo... |
Loy, Chen Change, 2024, "MMDetection3D", https://doi.org/10.21979/N9/15XUKI, DR-NTU (Data), V1
MMDetection3D is an open source object detection toolbox based on PyTorch, towards the next-generation platform for general 3D detection. It is a part of the OpenMMLab project. |
Aug 30, 2024 - Narendra VISHWAKARMA
Vishwakarma, Narendra, 2024, "Related Data for: Intelligent-reflecting-surfaces-assisted hybrid FSO/RF communication with diversity combining: a performance analysis", https://doi.org/10.21979/N9/XRDOTT, DR-NTU (Data), V1
MATLAB source code the publication title: "Intelligent-reflecting-surfaces-assisted hybrid FSO/RF communication with diversity combining: a performance analysis" These code will produce the outage probability and Bit error rate plots for the above paper |
Gao, Chuanchao; Kumar, Niraj; Easwaran, Arvind, 2024, "Replication Data for: Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing", https://doi.org/10.21979/N9/VJTMBM, DR-NTU (Data), V2, UNF:6:ujvYZ07RwxVvj5sepdEDNw== [fileUNF]
Experiment data for paper "Energy-Efficient Real-Time Job Mapping and Resource Management in Mobile-Edge Computing". |
Jul 3, 2024 - Safe ML
Yuhas, Michael John; Easwaran, Arvind, 2024, "Replication Data for: Co-Design of Out-of-Distribution Detectors for Autonomous Emergency Braking Systems", https://doi.org/10.21979/N9/YIOFK8, DR-NTU (Data), V2
Replication Data for: Co-Design of Out-of-Distribution Detectors for Autonomous Emergency Braking Systems |
