Search Results for author:
Found 32 papers, 3 papers with code
DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting
This point cloud serves as the initial state for the centroids of 3D Gaussians.
WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather
We propose a method to infer semantic segmentation maps from images captured under adverse weather conditions.
GT-Rain Single Image Deraining Challenge Report
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023.
Personalized Restoration via Dual-Pivot Tuning
This approach ensures that personalization does not interfere with the restoration process, resulting in a natural appearance with high fidelity to the person's identity and the attributes of the degraded image.
WeatherProof: A Paired-Dataset Approach to Semantic Segmentation in Adverse Weather
To this end, we create the WeatherProof Dataset, the first semantic segmentation dataset with accurate clear and adverse weather image pairs, which not only enables our new training paradigm, but also improves the evaluation of the performance gap between clear and degraded segmentation.
MVDD: Multi-View Depth Diffusion Models
State-of-the-art results from extensive experiments demonstrate MVDD's excellent ability in 3D shape generation, depth completion, and its potential as a 3D prior for downstream tasks.
Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields
In this work, we go one step further: in addition to radiance field rendering, we enable 3D Gaussian splatting on arbitrary-dimension semantic features via 2D foundation model distillation.
Enhancing Diffusion Models with 3D Perspective Geometry Constraints
We show that outputs of models trained with this constraint both appear more realistic and improve performance of downstream models trained on generated images.
SparseGS: Real-Time 360° Sparse View Synthesis using Gaussian Splatting
However, 3DGS still requires an abundance of training views to generate a coherent scene representation.
CG3D: Compositional Generation for Text-to-3D via Gaussian Splatting
With the onset of diffusion-based generative models and their ability to generate text-conditioned images, content generation has received a massive invigoration.
Making Thermal Imaging More Equitable and Accurate: Resolving Solar Loading Biases
Existing device manufacturers recommend that a subject who has been outdoors in sun re-acclimate to an indoor environment after a waiting period.
Synthetic Data in Healthcare
Synthetic data are becoming a critical tool for building artificially intelligent systems.
Depth Estimation From Camera Image and mmWave Radar Point Cloud
To fuse radar depth with an image, we propose a gated fusion scheme that accounts for the confidence scores of the correspondence so that we selectively combine radar and camera embeddings to yield a dense depth map.
WeatherStream: Light Transport Automation of Single Image Deweathering
We introduce a pipeline that uses the power of light-transport physics and a model trained on a small, initial seed dataset to reject approximately 99. 6% of unwanted scenes.
pCON: Polarimetric Coordinate Networks for Neural Scene Representations
Neural scene representations have achieved great success in parameterizing and reconstructing images, but current state of the art models are not optimized with the preservation of physical quantities in mind.
ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction
One school of thought is to encode a latent vector for each point (point latents).
MIME: Minority Inclusion for Majority Group Enhancement of AI Performance
A common misconception is that minority inclusion does not increase performance for majority groups alone.
Not Just Streaks: Towards Ground Truth for Single Image Deraining
We propose a large-scale dataset of real-world rainy and clean image pairs and a method to remove degradations, induced by rain streaks and rain accumulation, from the image.
Synthetic Generation of Face Videos With Plethysmograph Physiology
Accelerated by telemedicine, advances in Remote Photoplethysmography (rPPG) are beginning to offer a viable path toward non-contact physiological measurement.
Towards Rotation Invariance in Object Detection
Rotation augmentations generally improve a model's invariance/equivariance to rotation - except in object detection.
Overcoming Difficulty in Obtaining Dark-skinned Subjects for Remote-PPG by Synthetic Augmentation
Camera-based remote photoplethysmography (rPPG) provides a non-contact way to measure physiological signals (e. g., heart rate) using facial videos.
Enhancing Passive Non-Line-of-Sight Imaging Using Polarization Cues
This paper presents a method of passive non-line-of-sight (NLOS) imaging using polarization cues.
Visual Physics: Discovering Physical Laws from Videos
In this paper, we teach a machine to discover the laws of physics from video streams.
Blending Diverse Physical Priors with Neural Networks
Such generalization would require an architecture that can adapt to variations in the correctness of the physics, or in the quality of training data.
Deep Shape from Polarization
This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the realm of deep learning.
Macroscopic Interferometry: Rethinking Depth Estimation With Frequency-Domain Time-Of-Flight
A form of meter-scale, macroscopic interferometry is proposed using conventional time-of-flight (ToF) sensors.
Shape from Mixed Polarization
In this paper, we propose a new method that jointly uses viewpoint and polarization data to holistically separate diffuse and specular components, recover refractive index, and ultimately recover 3D shape.
Polarized 3D: High-Quality Depth Sensing With Polarization Cues
We propose a framework to overcome these key challenges, allowing the benefits of polarization to be used to enhance depth maps.
A Light Transport Model for Mitigating Multipath Interference in Time-of-Flight Sensors
Continuous-wave Time-of-flight (TOF) range imaging has become a commercially viable technology with many applications in computer vision and graphics.
Frequency Domain TOF: Encoding Object Depth in Modulation Frequency
Time of flight cameras may emerge as the 3-D sensor of choice.
A Light Transport Model for Mitigating Multipath Interference in TOF Sensors
Continuous-wave Time-of-flight (TOF) range imaging has become a commercially viable technology with many applications in computer vision and graphics.
Resolving Multi-path Interference in Time-of-Flight Imaging via Modulation Frequency Diversity and Sparse Regularization
Time-of-flight (ToF) cameras calculate depth maps by reconstructing phase shifts of amplitude-modulated signals.
