S-Lab for Advanced Intelligence, established in 2020, is a university laboratory at NTU focusing on research and development of cutting-edge AI technologies in computer vision, natural language processing, reinforcement learning, deep learning, and distributed computing. We aim to create impactful applications spanning various strategic areas in partnership with academic, industry, and government organizations.
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1 to 10 of 14 Results
layerbench.zip
Sep 11, 2025 - Trans-Adapter: A Plug-and-Play Framework for Transparent Image Inpainting
ZIP Archive - 654.6 MB - MD5: 972cfdcaec94978b658a7296d3bc0dbb
Benchmark of our paper.
OctoGibsonDataset.zip
Oct 8, 2024 - Octopus: Embodied Vision-Language Programmer from Environmental Feedback
ZIP Archive - 6.3 GB - MD5: df5972717c2859d34b4fadd702476a70
VToonify_cameral_ready.pdf
Oct 1, 2024 - VToonify
Adobe PDF - 4.6 MB - MD5: 8ac626f4963bc362583fd550a84c0a45
ProxyCLIP.pdf
Sep 25, 2024 - ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
Adobe PDF - 3.5 MB - MD5: 396eed51abcc20b34e2a977c570d33ee
ClearCLIP.pdf
Sep 25, 2024 - ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference
Adobe PDF - 4.7 MB - MD5: ef5b43ea1ec6f6fa4a3204222101b526
OpenVoc_SAM.pdf
Sep 25, 2024 - Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes Interactively
Adobe PDF - 3.4 MB - MD5: fa2b0303cf17c6b247314d2a9252040d
ClusteringSDF Self-Organized Neural Implicit Surfaces for 3D Decomposition.pdf
Sep 25, 2024 - ClusteringSDF: Self-Organized Neural Implicit Surfaces for 3D Decomposition
Adobe PDF - 5.7 MB - MD5: b796cd399fb8241b429ce3943ca1a23b
Neuparam_ECCV24.pdf
Sep 25, 2024 - Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering
Adobe PDF - 9.4 MB - MD5: a85b602783d50cc3f5c9166ddd818e79
Paper_ECCV2024.pdf
Sep 25, 2024 - Eliminating Feature Ambiguity for Few-Shot Segmentation
Adobe PDF - 1.4 MB - MD5: c46baf03e693a12c36592bb3f0ac214a
KEEP_ECCV.pdf
Sep 25, 2024 - Kalman-Inspired Feature Propagation for Video Face Super-Resolution
Adobe PDF - 7.8 MB - MD5: d6b53c6b690e3cf6f3c5e34757ea7c8e
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