31 citations · 87 across the 34 of their papers we have counts for
38 papers
Quantum-Aware Key Rank for Side-Channel Attacks evaluation
Yevgen Kotukh
Side-channel attacks on block ciphers rarely recover the key outright: they leave a residual key space ordered by subkey posteriors, and evaluation laboratories report the key rank…
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…
Level-of-Token Diffusion
Kiyohiro Nakayama, Brian Chao, Jan Ackermann +5
Image and video diffusion models allocate equal computation to every region, even when the intended scene calls for varying levels of detail. The spatial distribution of detail can…
MeshFlow: Mesh Generation with Equivariant Flow Matching
Qi Sun, Kiyohiro Nakayama, Jing Nathan Yan +6
Meshes are among the most common 3D scene representations, but directly generating meshes is challenging because the representation contains important symmetries, including permuta…
Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing
Kiyohiro Nakayama, I-Chao Shen, Ruofan Liu +3
Practical garment design spans two modes: intuitive creation from high-level intent, such as a reference image or text description, and complex low-level editing across 2D sewing p…
SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training
Yang Zheng, Hao Tan, Kai Zhang +4
The rise of 3D Gaussian Splatting has revolutionized photorealistic 3D asset creation, yet a critical gap remains for their interactive refinement and editing. Existing approaches…
pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation
Hansheng Chen, Kai Zhang, Hao Tan +3
Few-step diffusion or flow-based generative models typically distill a velocity-predicting teacher into a student that predicts a shortcut towards denoised data. This format mismat…
Gaussian Mixture Flow Matching Models
Hansheng Chen, Kai Zhang, Hao Tan +5
Diffusion models approximate the denoising distribution as a Gaussian and predict its mean, whereas flow matching models reparameterize the Gaussian mean as flow velocity. However,…
Diffusion Self-Distillation for Zero-Shot Customized Image Generation
Shengqu Cai, Eric Chan, Yunzhi Zhang +3
Text-to-image diffusion models produce impressive results but are frustrating tools for artists who desire fine-grained control. For example, a common use case is to create images…
Buffer Anytime: Zero-Shot Video Depth and Normal from Image Priors
Zhengfei Kuang, Tianyuan Zhang, Kai Zhang +7
We present Buffer Anytime, a framework for estimation of depth and normal maps (which we call geometric buffers) from video that eliminates the need for paired video--depth and vid…
3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation
Hansheng Chen, Bokui Shen, Yulin Liu +7
Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D…
Flow as the Cross-Domain Manipulation Interface
Mengda Xu, Zhenjia Xu, Yinghao Xu +4
We present Im2Flow2Act, a scalable learning framework that enables robots to acquire real-world manipulation skills without the need of real-world robot training data. The key idea…
GazeFusion: Saliency-Guided Image Generation
Yunxiang Zhang, Nan Wu, Connor Z. Lin +2
Diffusion models offer unprecedented image generation power given just a text prompt. While emerging approaches for controlling diffusion models have enabled users to specify the d…
Super-resolution imaging using super-oscillatory diffractive neural networks
Hang Chen, Sheng Gao, Zejia Zhao +4
Optical super-oscillation enables far-field super-resolution imaging beyond diffraction limits. However, the existing super-oscillatory lens for the spatial super-resolution imagin…
Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videos
Colton Stearns, Adam Harley, Mikaela Uy +4
Gaussian splatting has become a popular representation for novel-view synthesis, exhibiting clear strengths in efficiency, photometric quality, and compositional edibility. Followi…
MegaScenes: Scene-Level View Synthesis at Scale
Joseph Tung, Gene Chou, Ruojin Cai +5
Scene-level novel view synthesis (NVS) is fundamental to many vision and graphics applications. Recently, pose-conditioned diffusion models have led to significant progress by extr…
Interpreting the Weight Space of Customized Diffusion Models
Amil Dravid, Yossi Gandelsman, Kuan-Chieh Wang +4
We investigate the space of weights spanned by a large collection of customized diffusion models. We populate this space by creating a dataset of over 60,000 models, each of which…
3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang +4
Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This…
Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control
Zhengfei Kuang, Shengqu Cai, Hao He +4
Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation…
Evolutive Rendering Models
Fangneng Zhan, Hanxue Liang, Yifan Wang +6
The landscape of computer graphics has undergone significant transformations with the recent advances of differentiable rendering models. These rendering models often rely on heuri…
PhysAvatar: Learning the Physics of Dressed 3D Avatars from Visual Observations
Yang Zheng, Qingqing Zhao, Guandao Yang +8
Modeling and rendering photorealistic avatars is of crucial importance in many applications. Existing methods that build a 3D avatar from visual observations, however, struggle to…
Flying with Photons: Rendering Novel Views of Propagating Light
Anagh Malik, Noah Juravsky, Ryan Po +3
We present an imaging and neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. Our approach relies…
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
Hao He, Yinghao Xu, Yuwei Guo +4
Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that s…
GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation
Yinghao Xu, Zifan Shi, Wang Yifan +5
We introduce GRM, a large-scale reconstructor capable of recovering a 3D asset from sparse-view images in around 0.1s. GRM is a feed-forward transformer-based model that efficientl…