101 to 110 of 349 Results
Sep 25, 2024 - S-Lab for Advanced Intelligence
Lan, Mengcheng; Chen, Chaofeng; Ke, Yiping; Wang, Xinjiang; Feng, Litong; Zhang, Wayne, 2024, "ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation", https://doi.org/10.21979/N9/YY8L5O, DR-NTU (Data), V1
Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels. While Contrastive Language-Image Pre-training (CLIP) models shine in recognizing visual concepts from text, they often struggle with segment... |
Sep 25, 2024 - S-Lab for Advanced Intelligence
Lan, Mengcheng; Chen, Chaofeng; Ke, Yiping; Wang, Xinjiang; Feng, Litong; Zhang, Wayne, 2024, "ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference", https://doi.org/10.21979/N9/S6NTDJ, DR-NTU (Data), V1
Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains challenging, producing noisy segmentation maps with mis-segmented regions. In this paper, we carefully... |
Sep 25, 2024 - XU Bowen
New, T. H.; Xu, Bowen; Shi, Shengxian, 2024, "Replication Data for: Collisions of vortex rings with hemispheres", https://doi.org/10.21979/N9/0MLY8J, DR-NTU (Data), V1
The data support the findings in the paper of "Collisions of vortex rings with hemispheres". |
Sep 25, 2024 - S-Lab for Advanced Intelligence
Yuan, Haobo; Li, Xiangtai; Zhou, Chong; Li, Yining; Chen, Kai; Loy, Chen Change, 2024, "Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes Interactively", https://doi.org/10.21979/N9/L05ULT, DR-NTU (Data), V1
The CLIP and Segment Anything Model (SAM) are remarkable vision foundation models (VFMs). SAM excels in segmentation tasks across diverse domains, whereas CLIP is renowned for its zero-shot recognition capabilities. This paper presents an in-depth exploration of integrating these... |
Sep 25, 2024 - S-Lab for Advanced Intelligence
Wu, Tianhao; Zheng, Chuanxia; Wu, Qianyi; Cham, Tat-Jen, 2024, "ClusteringSDF: Self-Organized Neural Implicit Surfaces for 3D Decomposition", https://doi.org/10.21979/N9/RJUHMC, DR-NTU (Data), V1
3D decomposition/segmentation remains a challenge as large-scale 3D annotated data is not readily available. Existing approaches typically leverage 2D machine-generated segments, integrating them to achieve 3D consistency. In this paper, we propose ClusteringSDF, a novel approach... |
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 25, 2024 - Sreelakshmi CHERUVALLI
Regina, Viduthalai Rasheedkhan; Cheruvalli, Sreelakshmi; Kwok, Weihao; Chopra, Tarun; Rice, Scott, 2024, "Related data for: Decoding scalp health and microbiome dysbiosis", https://doi.org/10.21979/N9/A1SDY5, DR-NTU (Data), V1
Microbial colonization in hair follicles was investigated by direct imaging using scanning electron microscope. |
