3 citations · 15 across the 25 of their papers we have counts for
25 papers
Composite Classifier-Free Guidance for Multi-Modal Conditioning in Wind Dynamics Super-Resolution
Jacob Schnell, Aditya Makkar, Gunadi Gani +5
Various weather modelling problems (e.g., weather forecasting, optimizing turbine placements, etc.) require ample access to high-resolution, highly accurate wind data. Acquiring su…
SCALEX: Scalable Concept and Latent Exploration for Diffusion Models
E. Zhixuan Zeng, Yuhao Chen, Alexander Wong
Image generation models frequently encode social biases, including stereotypes tied to gender, race, and profession. Existing methods for analyzing these biases in diffusion models…
GraphPad: Inference-Time 3D Scene Graph Updates for Embodied Question Answering
Muhammad Qasim Ali, Saeejith Nair, Alexander Wong +2
Structured scene representations are a core component of embodied agents, helping to consolidate raw sensory streams into readable, modular, and searchable formats. Due to their hi…
SAMJAM: Zero-Shot Video Scene Graph Generation for Egocentric Kitchen Videos
Joshua Li, Fernando Jose Pena Cantu, Emily Yu +3
Video Scene Graph Generation (VidSGG) is an important topic in understanding dynamic kitchen environments. Current models for VidSGG require extensive training to produce scene gra…
Decoding Diffusion: A Scalable Framework for Unsupervised Analysis of Latent Space Biases and Representations Using Natural Language Prompts
E. Zhixuan Zeng, Yuhao Chen, Alexander Wong
Recent advances in image generation have made diffusion models powerful tools for creating high-quality images. However, their iterative denoising process makes understanding and i…
MetaFood3D: 3D Food Dataset with Nutrition Values
Yuhao Chen, Jiangpeng He, Gautham Vinod +11
Food computing is both important and challenging in computer vision (CV). It significantly contributes to the development of CV algorithms due to its frequent presence in datasets…
MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results
Jiangpeng He, Yuhao Chen, Gautham Vinod +16
The increasing interest in computer vision applications for nutrition and dietary monitoring has led to the development of advanced 3D reconstruction techniques for food items. How…
Understanding the Limitations of Diffusion Concept Algebra Through Food
E. Zhixuan Zeng, Yuhao Chen, Alexander Wong
Image generation techniques, particularly latent diffusion models, have exploded in popularity in recent years. Many techniques have been developed to manipulate and clarify the se…
NutritionVerse-Direct: Exploring Deep Neural Networks for Multitask Nutrition Prediction from Food Images
Matthew Keller, Chi-en Amy Tai, Yuhao Chen +2
Many aging individuals encounter challenges in effectively tracking their dietary intake, exacerbating their susceptibility to nutrition-related health complications. Self-reportin…
How Much You Ate? Food Portion Estimation on Spoons
Aaryam Sharma, Chris Czarnecki, Yuhao Chen +3
Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring throug…
In The Wild Ellipse Parameter Estimation for Circular Dining Plates and Bowls
Akil Pathiranage, Chris Czarnecki, Yuhao Chen +3
Ellipse estimation is an important topic in food image processing because it can be leveraged to parameterize plates and bowls, which in turn can be used to estimate camera view an…
Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement
Dayou Mao, Yuhao Chen, Yifan Wu +2
One of the main motivations of MTL is to develop neural networks capable of inferring multiple tasks simultaneously. While countless methods have been proposed in the past decade i…
NutritionVerse-Real: An Open Access Manually Collected 2D Food Scene Dataset for Dietary Intake Estimation
Chi-en Amy Tai, Saeejith Nair, Olivia Markham +4
Dietary intake estimation plays a crucial role in understanding the nutritional habits of individuals and populations, aiding in the prevention and management of diet-related healt…
NutritionVerse-Synth: An Open Access Synthetically Generated 2D Food Scene Dataset for Dietary Intake Estimation
Saeejith Nair, Chi-en Amy Tai, Yuhao Chen +1
Manually tracking nutritional intake via food diaries is error-prone and burdensome. Automated computer vision techniques show promise for dietary monitoring but require large and…
FoodFusion: A Latent Diffusion Model for Realistic Food Image Generation
Olivia Markham, Yuhao Chen, Chi-en Amy Tai +1
Current state-of-the-art image generation models such as Latent Diffusion Models (LDMs) have demonstrated the capacity to produce visually striking food-related images. However, th…
Cancer-Net PCa-Gen: Synthesis of Realistic Prostate Diffusion Weighted Imaging Data via Anatomic-Conditional Controlled Latent Diffusion
Aditya Sridhar, Chi-en Amy Tai, Hayden Gunraj +2
In Canada, prostate cancer is the most common form of cancer in men and accounted for 20% of new cancer cases for this demographic in 2022. Due to recent successes in leveraging ma…
NAS-NeRF: Generative Neural Architecture Search for Neural Radiance Fields
Saeejith Nair, Yuhao Chen, Mohammad Javad Shafiee +1
Neural radiance fields (NeRFs) enable high-quality novel view synthesis, but their high computational complexity limits deployability. While existing neural-based solutions strive…
NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches
Chi-en Amy Tai, Matthew Keller, Saeejith Nair +8
Accurate dietary intake estimation is critical for informing policies and programs to support healthy eating, as malnutrition has been directly linked to decreased quality of life.…
Continuous-Time Channel Prediction Based on Tensor Neural Ordinary Differential Equation
Mingyao Cui, Hao Jiang, Yuhao Chen +2
Channel prediction is critical to address the channel aging issue in mobile scenarios. Existing channel prediction techniques are mainly designed for discrete channel prediction, w…
Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions
Grant Sinha, Krish Parmar, Hilda Azimi +4
Food image segmentation is an important task that has ubiquitous applications, such as estimating the nutritional value of a plate of food. Although machine learning models have be…
Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge
Alexander Wong, Yifan Wu, Saad Abbasi +3
Multi-task learning has shown considerable promise for improving the performance of deep learning-driven vision systems for the purpose of robotic grasping. However, high architect…
NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food Models
Chi-en Amy Tai, Jason Li, Sriram Kumar +4
With the growth in capabilities of generative models, there has been growing interest in using photo-realistic renders of common 3D food items to improve downstream tasks such as f…
NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation
Chi-en Amy Tai, Matthew Keller, Mattie Kerrigan +4
77% of adults over 50 want to age in place today, presenting a major challenge to ensuring adequate nutritional intake. It has been reported that one in four older adults that are…
ShapeShift: Superquadric-based Object Pose Estimation for Robotic Grasping
E. Zhixuan Zeng, Yuhao Chen, Alexander Wong
Object pose estimation is a critical task in robotics for precise object manipulation. However, current techniques heavily rely on a reference 3D object, limiting their generalizab…