3 citations · 9 across the 12 of their papers we have counts for
17 papers
PCAsplat: Gaussian Splatting with Local PCA Regularization
Vitor Matias, Filipe Nascimento, Kiyohiro Nakayama +6
Gaussian splatting has emerged as a flexible representation for 3D reconstruction from posed images. However, existing methods are optimized primarily using rasterization-based los…
Where MLLMs Fail and Why: Causal Task Decomposition for Capability Failure Diagnosis
Xia Hu, Brian Potetz, Chun-Ta Lu +6
End-to-end accuracy on compositional tasks records how often MLLMs fail, but cannot distinguish whether a failure reflects an intrinsic deficit in the targeted capability or a casc…
UniPose9D: Universal Category-Agnostic Object Pose Estimation
Yang You, Yi Du, Cole Harrison +1
Object pose estimation is a fundamental problem in 3D vision. Although recent state-of-the-art approaches achieve strong performance, generalization to novel categories and unseen…
The Cartesian Shortcut: Re-evaluate Vision Reasoning in Polar Coordinate Space
Xia Hu, Zhenrui Yue, Brian Potetz +4
As current Multimodal Large Language Models rapidly saturate canonical visual reasoning benchmarks, a key question emerges: do these strong scores genuinely reflect robust visual u…
Asymmetric Flow Models
Hansheng Chen, Jan Ackermann, Minseo Kim +2
Flow-based generation in high-dimensional spaces is difficult because velocity prediction requires modeling high-dimensional noise, even when data has strong low-rank structure. We…
OCH3R: Object-Centric Holistic 3D Reconstruction
Yi Du, Yang You, Xiang Wan +1
Object-centric scene understanding is a fundamental challenge in computer vision. Existing approaches often rely on multi-stage pipelines that first apply pre-trained segmentors to…
Global Motion Corresponder for 3D Point-Based Scene Interpolation under Large Motion
Junru Lin, Chirag Vashist, Mikaela Angelina Uy +4
Existing dynamic scene interpolation methods typically assume that the motion between consecutive timesteps is small enough so that displacements can be locally approximated by lin…
Mixture of Contexts for Long Video Generation
Shengqu Cai, Ceyuan Yang, Lvmin Zhang +10
Long video generation is fundamentally a long context memory problem: models must retain and retrieve salient events across a long range without collapsing or drifting. However, sc…
Perspective-Aware Reasoning in Vision-Language Models via Mental Imagery Simulation
Phillip Y. Lee, Jihyeon Je, Chanho Park +3
We present a framework for perspective-aware reasoning in vision-language models (VLMs) through mental imagery simulation. Perspective-taking, the ability to perceive an environmen…
GenAnalysis: Joint Shape Analysis by Learning Man-Made Shape Generators with Deformation Regularizations
Yuezhi Yang, Haitao Yang, Kiyohiro Nakayama +3
We present GenAnalysis, an implicit shape generation framework that allows joint analysis of man-made shapes, including shape matching and joint shape segmentation. The key idea is…
Monocular Dynamic Gaussian Splatting: Fast, Brittle, and Scene Complexity Rules
Yiqing Liang, Mikhail Okunev, Mikaela Angelina Uy +4
Gaussian splatting methods are emerging as a popular approach for converting multi-view image data into scene representations that allow view synthesis. In particular, there is int…
ArtVLM: Attribute Recognition Through Vision-Based Prefix Language Modeling
William Yicheng Zhu, Keren Ye, Junjie Ke +4
Recognizing and disentangling visual attributes from objects is a foundation to many computer vision applications. While large vision language representations like CLIP had largely…
Img2CAD: Reverse Engineering 3D CAD Models from Images through VLM-Assisted Conditional Factorization
Yang You, Mikaela Angelina Uy, Jiaqi Han +7
Reverse engineering 3D computer-aided design (CAD) models from images is an important task for many downstream applications including interactive editing, manufacturing, architectu…
PASTA: Controllable Part-Aware Shape Generation with Autoregressive Transformers
Songlin Li, Despoina Paschalidou, Leonidas Guibas
The increased demand for tools that automate the 3D content creation process led to tremendous progress in deep generative models that can generate diverse 3D objects of high fidel…
ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Field
Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You +2
Neural radiance fields (NeRFs) have gained popularity with multiple works showing promising results across various applications. However, to the best of our knowledge, existing wor…
OptCtrlPoints: Finding the Optimal Control Points for Biharmonic 3D Shape Deformation
Kunho Kim, Mikaela Angelina Uy, Despoina Paschalidou +3
We propose OptCtrlPoints, a data-driven framework designed to identify the optimal sparse set of control points for reproducing target shapes using biharmonic 3D shape deformation.…
NeRF Revisited: Fixing Quadrature Instability in Volume Rendering
Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang +3
Neural radiance fields (NeRF) rely on volume rendering to synthesize novel views. Volume rendering requires evaluating an integral along each ray, which is numerically approximated…