1 citations · 1 across the 8 of their papers we have counts for
9 papers
DDMS: Discriminative Distillation of Multi-view Foundational Features into Single-view Models
Jeong-gi Kwak, Sho Kagami, Yuki Ono +1
Foundational visual features such as DINO have played a critical role across modern computer vision, and have recently become key components in multi-view feed-forward geometry est…
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…
Making Video Models Adhere to User Intent with Minor Adjustments
Daniel Ajisafe, Eric Hedlin, Helge Rhodin +1
With the recent drastic advancements in text-to-video diffusion models, controlling their generations has drawn interest. A popular way for control is through bounding boxes or lay…
SONIC: Spectral Optimization of Noise for Inpainting with Consistency
Seungyeon Baek, Erqun Dong, Shadan Namazifard +2
We propose a novel training-free method for inpainting with off-the-shelf text-to-image models. While guidance-based methods in theory allow generic models to be used for inverse p…
ROODI: Reconstructing Occluded Objects with Denoising Inpainters
Yeonjin Chang, Erqun Dong, Seunghyeon Seo +2
While the quality of novel-view images has improved dramatically with 3D Gaussian Splatting, extracting specific objects from scenes remains challenging. Isolating individual 3D Ga…
HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories
Eric Hedlin, Munawar Hayat, Fatih Porikli +2
To efficiently adapt large models or to train generative models of neural representations, Hypernetworks have drawn interest. While hypernetworks work well, training them is cumber…
NESI: Shape Representation via Neural Explicit Surface Intersection
Congyi Zhang, Jinfan Yang, Eric Hedlin +5
Compressed representations of 3D shapes that are compact, accurate, and can be processed efficiently directly in compressed form, are extremely useful for digital media application…
Prompting Hard or Hardly Prompting: Prompt Inversion for Text-to-Image Diffusion Models
Shweta Mahajan, Tanzila Rahman, Kwang Moo Yi +1
The quality of the prompts provided to text-to-image diffusion models determines how faithful the generated content is to the user's intent, often requiring `prompt engineering'. T…
ViVid-1-to-3: Novel View Synthesis with Video Diffusion Models
Jeong-gi Kwak, Erqun Dong, Yuhe Jin +3
Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering…