4 citations · 6 across the 8 of their papers we have counts for
6 papers · 1 filter
CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models
He Liang, Chenyang Ma, Yiming Zhang +4
Existing 3D scene-grounded Large Language Models (3D-LLMs) focus on answering questions grounded in simplified single-room 3D scenes, lacking the ability to reason over real-world…
A non-invasive video-based method for individual identification of wildlife using gait dynamics
Muhammad Aamir, Matthew Wijers, Sangyun Shin +2
Gait is a distinctive behavioral characteristic that enables non-invasive individual identification without requiring physical interaction with an animal. While gait-based analysis…
WildDepth: A Multimodal Dataset for 3D Wildlife Perception and Depth Estimation
Muhammad Aamir, Naoya Muramatsu, Sangyun Shin +6
Depth estimation and 3D reconstruction have been extensively studied as core topics in computer vision. Starting from rigid objects with relatively simple geometric shapes, such as…
Dusk Till Dawn: Self-supervised Nighttime Stereo Depth Estimation using Visual Foundation Models
Madhu Vankadari, Samuel Hodgson, Sangyun Shin +2
Self-supervised depth estimation algorithms rely heavily on frame-warping relationships, exhibiting substantial performance degradation when applied in challenging circumstances, s…
Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation
Sangyun Shin, Kaichen Zhou, Madhu Vankadari +2
Coarse-to-fine 3D instance segmentation methods show weak performances compared to recent Grouping-based, Kernel-based and Transformer-based methods. We argue that this is due to t…
DynPoint: Dynamic Neural Point For View Synthesis
Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin +4
The introduction of neural radiance fields has greatly improved the effectiveness of view synthesis for monocular videos. However, existing algorithms face difficulties when dealin…