8 citations · 14 across the 9 of their papers we have counts for
6 papers · 1 filter
SplArt: Articulation Estimation and Part-Level Reconstruction with 3D Gaussian Splatting
Shengjie Lin, Jiading Fang, Muhammad Zubair Irshad +4
Reconstructing articulated objects prevalent in daily environments is crucial for applications in augmented/virtual reality and robotics. However, existing methods face scalability…
Transcrib3D: 3D Referring Expression Resolution through Large Language Models
Jiading Fang, Xiangshan Tan, Shengjie Lin +6
If robots are to work effectively alongside people, they must be able to interpret natural language references to objects in their 3D environment. Understanding 3D referring expres…
NeRFuser: Large-Scale Scene Representation by NeRF Fusion
Jiading Fang, Shengjie Lin, Igor Vasiljevic +5
A practical benefit of implicit visual representations like Neural Radiance Fields (NeRFs) is their memory efficiency: large scenes can be efficiently stored and shared as small ne…
DeLiRa: Self-Supervised Depth, Light, and Radiance Fields
Vitor Guizilini, Igor Vasiljevic, Jiading Fang +4
Differentiable volumetric rendering is a powerful paradigm for 3D reconstruction and novel view synthesis. However, standard volume rendering approaches struggle with degenerate ge…
Depth Field Networks for Generalizable Multi-view Scene Representation
Vitor Guizilini, Igor Vasiljevic, Jiading Fang +4
Modern 3D computer vision leverages learning to boost geometric reasoning, mapping image data to classical structures such as cost volumes or epipolar constraints to improve matchi…
Self-Supervised Camera Self-Calibration from Video
Jiading Fang, Igor Vasiljevic, Vitor Guizilini +4
Camera calibration is integral to robotics and computer vision algorithms that seek to infer geometric properties of the scene from visual input streams. In practice, calibration i…