5 citations · 8 across the 10 of their papers we have counts for
10 papers
LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory
Junyi Zhang, Charles Herrmann, Junhwa Hur +5
Feedforward geometric foundation models achieve strong short-window reconstruction, yet scaling them to minutes-long videos is bottlenecked by quadratic attention complexity or lim…
MotionV2V: Editing Motion in a Video
Ryan Burgert, Charles Herrmann, Forrester Cole +4
While generative video models have achieved remarkable fidelity and consistency, applying these capabilities to video editing remains a complex challenge. Recent research has explo…
MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos
Zhengqi Li, Richard Tucker, Forrester Cole +6
We present a system that allows for accurate, fast, and robust estimation of camera parameters and depth maps from casual monocular videos of dynamic scenes. Most conventional stru…
Motion Prompting: Controlling Video Generation with Motion Trajectories
Daniel Geng, Charles Herrmann, Junhwa Hur +11
Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text prompts for control, which stru…
Generative Omnimatte: Learning to Decompose Video into Layers
Yao-Chih Lee, Erika Lu, Sarah Rumbley +4
Given a video and a set of input object masks, an omnimatte method aims to decompose the video into semantically meaningful layers containing individual objects along with their as…
VidPanos: Generative Panoramic Videos from Casual Panning Videos
Jingwei Ma, Erika Lu, Roni Paiss +6
Panoramic image stitching provides a unified, wide-angle view of a scene that extends beyond the camera's field of view. Stitching frames of a panning video into a panoramic photog…
MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion
Junyi Zhang, Charles Herrmann, Junhwa Hur +5
Estimating geometry from dynamic scenes, where objects move and deform over time, remains a core challenge in computer vision. Current approaches often rely on multi-stage pipeline…
ExtraNeRF: Visibility-Aware View Extrapolation of Neural Radiance Fields with Diffusion Models
Meng-Li Shih, Wei-Chiu Ma, Lorenzo Boyice +4
We propose ExtraNeRF, a novel method for extrapolating the range of views handled by a Neural Radiance Field (NeRF). Our main idea is to leverage NeRFs to model scene-specific, fin…
DreamWalk: Style Space Exploration using Diffusion Guidance
Michelle Shu, Charles Herrmann, Richard Strong Bowen +2
Text-conditioned diffusion models can generate impressive images, but fall short when it comes to fine-grained control. Unlike direct-editing tools like Photoshop, text conditioned…
ZipLoRA: Any Subject in Any Style by Effectively Merging LoRAs
Viraj Shah, Nataniel Ruiz, Forrester Cole +4
Methods for finetuning generative models for concept-driven personalization generally achieve strong results for subject-driven or style-driven generation. Recently, low-rank adapt…