10 citations · 16 across the 19 of their papers we have counts for
25 papers
RoboCloth: A Large-Scale Real Cloth Material Dataset for Neural Reflectance Reconstruction
Zhen Li, Haoran Qin, Francesco Di Sario +2
We present RoboCloth, a dataset of 500 real cloth materials captured under flexible, calibrated camera and lighting configurations, where both are robotically controlled during acq…
ORBIT++: Benchmarking SfM in the Wild with 360° Video
Sara Sabour, Linyi Jin, Richard Tucker +9
Structure-from-Motion (SfM) is a cornerstone of 3D perception, yet current methods often fail when applied to complex videos involving challenging camera motions or dynamic scenes.…
Remember to be Curious: Episodic Context and Persistent Worlds for 3D Exploration
Lily Goli, Justin Kerr, Daniele Reda +3
Exploration is a prerequisite for learning useful behaviors in sparse-reward, long-horizon tasks, particularly within 3D environments. Curiosity-driven reinforcement learning addre…
Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction
Ahan Shabanov, Peter Hedman, Ethan Weber +10
We present Free-Range Gaussians, a multi-view reconstruction method that predicts non-pixel, non-voxel-aligned 3D Gaussians from as few as four images. This is done through flow ma…
FullCircle: Effortless 3D Reconstruction from Casual 360 Captures
Yalda Foroutan, Ipek Oztas, Daniel Rebain +4
Radiance fields have emerged as powerful tools for 3D scene reconstruction. However, casual capture remains challenging due to the narrow field of view of perspective cameras, whic…
Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields
Weihan Luo, Lily Goli, Sherwin Bahmani +3
Modeling the time-varying 3D appearance of plants during growth poses unique challenges: unlike most dynamic scenes, plants continuously generate new geometry as they expand, branc…
360Anything: Geometry-Free Lifting of Images and Videos to 360°
Ziyi Wu, Daniel Watson, Andrea Tagliasacchi +3
Lifting perspective images and videos to 360° panoramas enables immersive 3D world generation. Existing approaches often rely on explicit geometric alignment between the perspectiv…
Nexels: Neurally-Textured Surfels for Real-Time Novel View Synthesis with Sparse Geometries
Victor Rong, Jan Held, Victor Chu +5
Though Gaussian splatting has achieved impressive results in novel view synthesis, it requires millions of primitives to model highly textured scenes, even when the geometry of the…
MeshSplatting: Differentiable Rendering with Opaque Meshes
Jan Held, Sanghyun Son, Renaud Vandeghen +7
Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain in…
Spherical Voronoi: Directional Appearance as a Differentiable Partition of the Sphere
Francesco Di Sario, Daniel Rebain, Dor Verbin +2
Radiance field methods (e.g. 3D Gaussian Splatting) have emerged as a powerful paradigm for novel view synthesis, yet their appearance modeling often relies on Spherical Harmonics…
Hierarchical Transformers for Unsupervised 3D Shape Abstraction
Aditya Vora, Lily Goli, Andrea Tagliasacchi +1
We introduce HiT, a novel hierarchical neural field representation for 3D shapes that learns general hierarchies in a coarse-to-fine manner across different shape categories in an…
Triangle Splatting+: Differentiable Rendering with Opaque Triangles
Jan Held, Renaud Vandeghen, Sanghyun Son +6
Reconstructing 3D scenes and synthesizing novel views has seen rapid progress in recent years. Neural Radiance Fields demonstrated that continuous volumetric radiance fields can ac…
Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation
Sherwin Bahmani, Tianchang Shen, Jiawei Ren +10
The ability to generate virtual environments is crucial for applications ranging from gaming to physical AI domains such as robotics, autonomous driving, and industrial AI. Current…
3D Gaussian Flats: Hybrid 2D/3D Photometric Scene Reconstruction
Maria Taktasheva, Lily Goli, Alessandro Fiorini +3
Recent advances in radiance fields and novel view synthesis enable creation of realistic digital twins from photographs. However, current methods struggle with flat, texture-less s…
Triangle Splatting for Real-Time Radiance Field Rendering
Jan Held, Renaud Vandeghen, Adrien Deliege +7
The field of computer graphics was revolutionized by models such as Neural Radiance Fields and 3D Gaussian Splatting, displacing triangles as the dominant representation for photog…
StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting
Shakiba Kheradmand, Delio Vicini, George Kopanas +4
3D Gaussian splatting (3DGS) is a popular radiance field method, with many application-specific extensions. Most variants rely on the same core algorithm: depth-sorting of Gaussian…
RoMo: Robust Motion Segmentation Improves Structure from Motion
Lily Goli, Sara Sabour, Mark Matthews +6
There has been extensive progress in the reconstruction and generation of 4D scenes from monocular casually-captured video. While these tasks rely heavily on known camera poses, th…
AC3D: Analyzing and Improving 3D Camera Control in Video Diffusion Transformers
Sherwin Bahmani, Ivan Skorokhodov, Guocheng Qian +5
Numerous works have recently integrated 3D camera control into foundational text-to-video models, but the resulting camera control is often imprecise, and video generation quality…
SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting
Sara Sabour, Lily Goli, George Kopanas +6
3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However…
VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control
Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin +9
Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained con…
Controlling Space and Time with Diffusion Models
Daniel Watson, Saurabh Saxena, Lala Li +2
We present 4DiM, a cascaded diffusion model for 4D novel view synthesis (NVS), supporting generation with arbitrary camera trajectories and timestamps, in natural scenes, condition…
TC4D: Trajectory-Conditioned Text-to-4D Generation
Sherwin Bahmani, Xian Liu, Wang Yifan +9
Recent techniques for text-to-4D generation synthesize dynamic 3D scenes using supervision from pre-trained text-to-video models. However, existing representations for motion, such…
pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction
David Charatan, Sizhe Li, Andrea Tagliasacchi +1
We introduce pixelSplat, a feed-forward model that learns to reconstruct 3D radiance fields parameterized by 3D Gaussian primitives from pairs of images. Our model features real-ti…
4D-fy: Text-to-4D Generation Using Hybrid Score Distillation Sampling
Sherwin Bahmani, Ivan Skorokhodov, Victor Rong +7
Recent breakthroughs in text-to-4D generation rely on pre-trained text-to-image and text-to-video models to generate dynamic 3D scenes. However, current text-to-4D methods face a t…