4 citations · 7 across the 8 of their papers we have counts for
10 papers
PhysWAM: Physically Consistent World Action Model for Autonomous Driving
Dhruv Parikh, Fengcheng Yu, Quankai Gao +11
World-action models (WAMs) jointly predict how a scene will evolve and how an agent should act, however joint generation alone does not necessarily impose a shared geometric constr…
InstantSfM: Towards GPU-Native SfM for the Deep Learning Era
Jiankun Zhong, Zitong Zhan, Quankai Gao +6
Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critical upstream component for applica…
Can3Tok: Canonical 3D Tokenization and Latent Modeling of Scene-Level 3D Gaussians
Quankai Gao, Iliyan Georgiev, Tuanfeng Y. Wang +3
3D generation has made significant progress, however, it still largely remains at the object-level. Feedforward 3D scene-level generation has been rarely explored due to the lack o…
InSpaceType: Dataset and Benchmark for Reconsidering Cross-Space Type Performance in Indoor Monocular Depth
Cho-Ying Wu, Quankai Gao, Chin-Cheng Hsu +3
Indoor monocular depth estimation helps home automation, including robot navigation or AR/VR for surrounding perception. Most previous methods primarily experiment with the NYUv2 D…
Stratified Avatar Generation from Sparse Observations
Han Feng, Wenchao Ma, Quankai Gao +3
Estimating 3D full-body avatars from AR/VR devices is essential for creating immersive experiences in AR/VR applications. This task is challenging due to the limited input from Hea…
GaussianFlow: Splatting Gaussian Dynamics for 4D Content Creation
Quankai Gao, Qiangeng Xu, Zhe Cao +5
Creating 4D fields of Gaussian Splatting from images or videos is a challenging task due to its under-constrained nature. While the optimization can draw photometric reference from…
InSpaceType: Reconsider Space Type in Indoor Monocular Depth Estimation
Cho-Ying Wu, Quankai Gao, Chin-Cheng Hsu +3
Indoor monocular depth estimation has attracted increasing research interest. Most previous works have been focusing on methodology, primarily experimenting with NYU-Depth-V2 (NYUv…
Strivec: Sparse Tri-Vector Radiance Fields
Quankai Gao, Qiangeng Xu, Hao Su +2
We propose Strivec, a novel neural representation that models a 3D scene as a radiance field with sparsely distributed and compactly factorized local tensor feature grids. Our appr…
Controllable 3D Generative Adversarial Face Model via Disentangling Shape and Appearance
Fariborz Taherkhani, Aashish Rai, Quankai Gao +6
3D face modeling has been an active area of research in computer vision and computer graphics, fueling applications ranging from facial expression transfer in virtual avatars to sy…
Deep Graph Matching under Quadratic Constraint
Quankai Gao, Fudong Wang, Nan Xue +2
Recently, deep learning based methods have demonstrated promising results on the graph matching problem, by relying on the descriptive capability of deep features extracted on grap…