3.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nvidia (United Kingdom)GB136 papers
- Lawrence Berkeley National LaboratoryUS32 papers
- Stanford UniversityUS30 papers
- University of California, BerkeleyUS29 papers
- California Institute of TechnologyUS26 papers
- Massachusetts Institute of TechnologyUS25 papers
- Carnegie Mellon UniversityUS24 papers
- University of Illinois Urbana-ChampaignUS24 papers
- University of TorontoCA24 papers
- University of WashingtonUS23 papers
- Harvard UniversityUS19 papers
- Georgia Institute of TechnologyUS17 papers
117 papers · 1 filter
Make me an Expert: Distilling from Generalist Black-Box Models into Specialized Models for Semantic Segmentation
Yasser Benigmim, Subhankar Roy, Khalid Oublal +4
The rise of Artificial Intelligence as a Service (AIaaS) democratizes access to pre-trained models via Application Programming Interfaces (APIs), but also raises a fundamental ques…
Align 3D Representation and Text Embedding for 3D Content Personalization
Qi Song, Ziyuan Luo, Ka Chun Cheung +2
Recent advances in NeRF and 3DGS have significantly enhanced the efficiency and quality of 3D content synthesis. However, efficient personalization of generated 3D content remains…
SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes
Tianchang Shen, Zhaoshuo Li, Marc Law +5
Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or…
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-spe…
Filtering After Shading With Stochastic Texture Filtering
Matt Pharr, Bartlomiej Wronski, Marco Salvi +1
2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-q…
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
Francis Williams, Jiahui Huang, Jonathan Swartz +9
We present fVDB, a novel GPU-optimized framework for deep learning on large-scale 3D data. fVDB provides a complete set of differentiable primitives to build deep learning architec…
Simplicits: Mesh-Free, Geometry-Agnostic, Elastic Simulation
Vismay Modi, Nicholas Sharp, Or Perel +2
The proliferation of 3D representations, from explicit meshes to implicit neural fields and more, motivates the need for simulators agnostic to representation. We present a data-,…
DiffUHaul: A Training-Free Method for Object Dragging in Images
Omri Avrahami, Rinon Gal, Gal Chechik +4
Text-to-image diffusion models have proven effective for solving many image editing tasks. However, the seemingly straightforward task of seamlessly relocating objects within a sce…
SPAMming Labels: Efficient Annotations for the Trackers of Tomorrow
Orcun Cetintas, Tim Meinhardt, Guillem Brasó +1
Increasing the annotation efficiency of trajectory annotations from videos has the potential to enable the next generation of data-hungry tracking algorithms to thrive on large-sca…
Diffusion Model-Based Image Editing: A Survey
Yi Huang, Jiancheng Huang, Yifan Liu +7
Denoising diffusion models have emerged as a powerful tool for various image generation and editing tasks, facilitating the synthesis of visual content in an unconditional or input…
Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation
Mathis Petrovich, Or Litany, Umar Iqbal +4
Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prom…
All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes
Jose L. Gómez, Manuel Silva, Antonio Seoane +5
We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios. Developed using high-quality geometry and materials,…
TPA3D: Triplane Attention for Fast Text-to-3D Generation
Bin-Shih Wu, Hong-En Chen, Sheng-Yu Huang +1
Due to the lack of large-scale text-3D correspondence data, recent text-to-3D generation works mainly rely on utilizing 2D diffusion models for synthesizing 3D data. Since diffusio…
Inverse Global Illumination using a Neural Radiometric Prior
Saeed Hadadan, Geng Lin, Jan Novák +2
Inverse rendering methods that account for global illumination are becoming more popular, but current methods require evaluating and automatically differentiating millions of path…
Single-Shot Implicit Morphable Faces with Consistent Texture Parameterization
Connor Z. Lin, Koki Nagano, Jan Kautz +5
There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for ed…
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo +3
In this work, we present Conditional Adversarial Latent Models (CALM), an approach for generating diverse and directable behaviors for user-controlled interactive virtual character…
Learning to Relight Portrait Images via a Virtual Light Stage and Synthetic-to-Real Adaptation
Yu-Ying Yeh, Koki Nagano, Sameh Khamis +3
Given a portrait image of a person and an environment map of the target lighting, portrait relighting aims to re-illuminate the person in the image as if the person appeared in an…
Boosting Supervised Learning Performance with Co-training
Xinnan Du, William Zhang, Jose M. Alvarez
Deep learning perception models require a massive amount of labeled training data to achieve good performance. While unlabeled data is easy to acquire, the cost of labeling is proh…
Artificial Intelligence in PET: an Industry Perspective
Arkadiusz Sitek, Sangtae Ahn, Evren Asma +6
Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has t…
Tensor Methods in Computer Vision and Deep Learning
Yannis Panagakis, Jean Kossaifi, Grigorios G. Chrysos +4
Tensors, or multidimensional arrays, are data structures that can naturally represent visual data of multiple dimensions. Inherently able to efficiently capture structured, latent…
Robust Vision-Based Cheat Detection in Competitive Gaming
Aditya Jonnalagadda, Iuri Frosio, Seth Schneider +2
Game publishers and anti-cheat companies have been unsuccessful in blocking cheating in online gaming. We propose a novel, vision-based approach that captures the final state of th…
Camera Calibration with Pose Guidance
Yuzhuo Ren, Feng Hu
Camera calibration plays a critical role in various computer vision tasks such as autonomous driving or augmented reality. Widely used camera calibration tools utilize plane patter…
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
Vishwesh Nath, Dong Yang, Bennett A. Landman +2
Active learning is a unique abstraction of machine learning techniques where the model/algorithm could guide users for annotation of a set of data points that would be beneficial t…
Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation
Jingkun Chen, Wenqi Li, Hongwei Li +1
Multi-modal medical image segmentation plays an essential role in clinical diagnosis. It remains challenging as the input modalities are often not well-aligned spatially. Existing…