Search Results for author:
Found 38 papers, 16 papers with code
Driver Attention Tracking and Analysis
This network has a camera calibration module that can compute an embedding vector that represents the spatial configuration between the driver and the camera system.
FlexEdit: Flexible and Controllable Diffusion-based Object-centric Image Editing
Our work addresses limitations seen in previous approaches for object-centric editing problems, such as unrealistic results due to shape discrepancies and limited control in object replacement or insertion.
Blur2Blur: Blur Conversion for Unsupervised Image Deblurring on Unknown Domains
This algorithm works by transforming a blurry input image, which is challenging to deblur, into another blurry image that is more amenable to deblurring.
Time-Efficient and Identity-Consistent Virtual Try-On Using A Variant of Altered Diffusion Models
This study discusses the critical issues of Virtual Try-On in contemporary e-commerce and the prospective metaverse, emphasizing the challenges of preserving intricate texture details and distinctive features of the target person and the clothes in various scenarios, such as clothing texture and identity characteristics like tattoos or accessories.
OpenSUN3D: 1st Workshop Challenge on Open-Vocabulary 3D Scene Understanding
This report provides an overview of the challenge hosted at the OpenSUN3D Workshop on Open-Vocabulary 3D Scene Understanding held in conjunction with ICCV 2023.
EFHQ: Multi-purpose ExtremePose-Face-HQ dataset
The existing facial datasets, while having plentiful images at near frontal views, lack images with extreme head poses, leading to the downgraded performance of deep learning models when dealing with profile or pitched faces.
Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidance
We introduce Open3DIS, a novel solution designed to tackle the problem of Open-Vocabulary Instance Segmentation within 3D scenes.
Ranked #1 on
3D Open-Vocabulary Instance Segmentation
on S3DIS
3D Instance Segmentation
3D Open-Vocabulary Instance Segmentation
+4
SwiftBrush: One-Step Text-to-Image Diffusion Model with Variational Score Distillation
Despite their ability to generate high-resolution and diverse images from text prompts, text-to-image diffusion models often suffer from slow iterative sampling processes.
Stable Messenger: Steganography for Message-Concealed Image Generation
In the ever-expanding digital landscape, safeguarding sensitive information remains paramount.
Robust Diffusion GAN using Semi-Unbalanced Optimal Transport
Diffusion models, a type of generative model, have demonstrated great potential for synthesizing highly detailed images.
Ranked #5 on
Image Generation
on STL-10
SolarFormer: Multi-scale Transformer for Solar PV Profiling
Accurate mapping of PV installations is crucial for understanding their adoption and informing energy policy.
Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation
To address this, generative models have emerged as an effective solution for generating synthetic data.
UnsMOT: Unified Framework for Unsupervised Multi-Object Tracking with Geometric Topology Guidance
In this paper, we push forward the state-of-the-art performance of unsupervised MOT methods by proposing UnsMOT, a novel framework that explicitly combines the appearance and motion features of objects with geometric information to provide more accurate tracking.
Flow Matching in Latent Space
In this work, we propose to apply flow matching in the latent spaces of pretrained autoencoders, which offers improved computational efficiency and scalability for high-resolution image synthesis.
Ranked #4 on
Image Generation
on CelebA-HQ 256x256
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
In this tutorial, we aim to provide a holistic lens on emerging UQ methods for ML models with a particular focus on neural networks and the applications of these UQ methods in tackling engineering design as well as prognostics and health management problems.
HyperCUT: Video Sequence from a Single Blurry Image using Unsupervised Ordering
We consider the challenging task of training models for image-to-video deblurring, which aims to recover a sequence of sharp images corresponding to a given blurry image input.
Anti-DreamBooth: Protecting users from personalized text-to-image synthesis
Despite the complicated formulation of DreamBooth and Diffusion-based text-to-image models, our methods effectively defend users from the malicious use of those models.
Efficient Scale-Invariant Generator with Column-Row Entangled Pixel Synthesis
Any-scale image synthesis offers an efficient and scalable solution to synthesize photo-realistic images at any scale, even going beyond 2K resolution.
Medical Phrase Grounding with Region-Phrase Context Contrastive Alignment
To enable MedRPG to locate nuanced medical findings with better region-phrase correspondences, we further propose Tri-attention Context contrastive alignment (TaCo).
Marginal-Certainty-aware Fair Ranking Algorithm
In MCFair, we first develop a ranking objective that includes uncertainty, fairness, and user utility.
Wavelet Diffusion Models are fast and scalable Image Generators
Diffusion models are rising as a powerful solution for high-fidelity image generation, which exceeds GANs in quality in many circumstances.
Ranked #1 on
Image Generation
on CelebA-HQ 512x512
Monotonic Gaussian process for physics-constrained machine learning with materials science applications
Gaussian process (GP) is perhaps one of the most common methods in machine learning for small datasets.
Reinforcement Learning to Rank with Coarse-grained Labels
The results on simulated coarse-grained labeled dataset show that while using coarse-grained labels to train an RL model for LTR tasks still can not outperform traditional approaches using fine-grained labels, it still achieve somewhat promising results and is potentially helpful for future research in LTR.
Learning to Rank Rationales for Explainable Recommendation
Seeing this gap, we propose a model named Semantic-Enhanced Bayesian Personalized Explanation Ranking (SE-BPER) to effectively combine the interaction information and semantic information.
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data.
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Domain adaptation (DA) benefits from the rigorous theoretical works that study its insightful characteristics and various aspects, e. g., learning domain-invariant representations and its trade-off.
Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers
As a result, the proposed Scalable$^3$-BO framework is scalable in three independent perspectives: with respect to data size, dimensionality, and computational resource on HPC.
ULTRA: An Unbiased Learning To Rank Algorithm Toolbox
Our toolbox is an important resource for researchers to conduct experiments on ULTR algorithms with different configurations as well as testing their own algorithms with the supported features.
Progressive Semantic Segmentation
In this work, we present MagNet, a multi-scale framework that resolves local ambiguity by looking at the image at multiple magnification levels.
Ranked #3 on
Land Cover Classification
on DeepGlobe
Lipstick ain't enough: Beyond Color Matching for In-the-Wild Makeup Transfer
However, existing works overlooked the latter components and confined makeup transfer to color manipulation, focusing only on light makeup styles.
Ranked #1 on
Facial Makeup Transfer
on CPM-Synt-2
Explore Image Deblurring via Blur Kernel Space
This paper introduces a method to encode the blur operators of an arbitrary dataset of sharp-blur image pairs into a blur kernel space.
Blind Image Deblurring
Facial Expression Recognition (FER)
+1
FineNet: Frame Interpolation and Enhancement for Face Video Deblurring
The objective of this work is to deblur face videos.
WaNet -- Imperceptible Warping-based Backdoor Attack
With the thriving of deep learning and the widespread practice of using pre-trained networks, backdoor attacks have become an increasing security threat drawing many research interests in recent years.
Input-Aware Dynamic Backdoor Attack
In recent years, neural backdoor attack has been considered to be a potential security threat to deep learning systems.
srMO-BO-3GP: A sequential regularized multi-objective constrained Bayesian optimization for design applications
Finally, we couple the third GP along with the classical BO framework to promote the richness and diversity of the Pareto frontier by the exploitation and exploration acquisition function.
aphBO-2GP-3B: A budgeted asynchronous parallel multi-acquisition functions for constrained Bayesian optimization on high-performing computing architecture
First, the efficiency of the Bayesian optimization is improved, where multiple input locations are evaluated massively parallel in an asynchronous manner to accelerate the optimization convergence with respect to physical runtime.
Action Recognition in the Frequency Domain
In this paper, we describe a simple strategy for mitigating variability in temporal data series by shifting focus onto long-term, frequency domain features that are less susceptible to variability.
