Search Results for author:
Found 25 papers, 11 papers with code
Example-Guided Image Synthesis using Masked Spatial-Channel Attention and Self-Supervision
Example-guided image synthesis has recently been attempted to synthesize an image from a semantic label map and an exemplary image.
Jurassic World Remake: Bringing Ancient Fossils Back to Life via Zero-Shot Long Image-to-Image Translation
In this work, we use text-guided latent diffusion models for zero-shot image-to-image translation (I2I) across large domain gaps (longI2I), where large amounts of new visual features and new geometry need to be generated to enter the target domain.
Improving Video Colorization by Test-Time Tuning
With the advancements in deep learning, video colorization by propagating color information from a colorized reference frame to a monochrome video sequence has been well explored.
Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators
Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects.
Cross-Camera Deep Colorization
Our method takes cross-domain and cross-scale images as input, and consequently synthesizes HR colorization results to facilitate the trade-off between spatial-temporal resolution and color depth in the single-camera imaging system.
CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training
We propose cascaded modulation GAN (CM-GAN), a new network design consisting of an encoder with Fourier convolution blocks that extract multi-scale feature representations from the input image with holes and a dual-stream decoder with a novel cascaded global-spatial modulation block at each scale level.
Ranked #1 on
Image Inpainting
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Point Cloud Denoising via Momentum Ascent in Gradient Fields
To achieve point cloud denoising, traditional methods heavily rely on geometric priors, and most learning-based approaches suffer from outliers and loss of details.
MANet: Improving Video Denoising with a Multi-Alignment Network
In video denoising, the adjacent frames often provide very useful information, but accurate alignment is needed before such information can be harnassed.
SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing
Recently, large pretrained models (e. g., BERT, StyleGAN, CLIP) show great knowledge transfer and generalization capability on various downstream tasks within their domains.
SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Editing
Recently, large pretrained models (e. g., BERT, StyleGAN, CLIP) have shown great knowledge transfer and generalization capability on various downstream tasks within their domains.
Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis
The learned prototypes and their labels can be regarded as denoising features and labels for the local regions and can guide the training process to prevent the model from overfitting the noisy cases.
Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization
We propose to remove the bias information misused by the target task with a cross-sample adversarial debiasing (CSAD) method.
Semantic Layout Manipulation with High-Resolution Sparse Attention
A core problem of this task is how to transfer visual details from the input images to the new semantic layout while making the resulting image visually realistic.
Actor-Action Video Classification CSC 249/449 Spring 2020 Challenge Report
This technical report summarizes submissions and compiles from Actor-Action video classification challenge held as a final project in CSC 249/449 Machine Vision course (Spring 2020) at University of Rochester
Image Sentiment Transfer
In this paper, we propose an effective and flexible framework that performs image sentiment transfer at the object level.
Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach
In this work, we study the problem of personalized fashion recommendation from social media data, i. e. recommending new outfits to social media users that fit their fashion preferences.
What comprises a good talking-head video generation?: A Survey and Benchmark
In this work, we present a carefully-designed benchmark for evaluating talking-head video generation with standardized dataset pre-processing strategies.
Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision
Example-guided image synthesis has recently been attempted to synthesize an image from a semantic label map and an exemplary image.
Example-Guided Scene Image Synthesis using Masked Spatial-Channel Attention and Patch-Based Self-Supervision
Example-guided image synthesis has been recently attempted to synthesize an image from a semantic label map and an exemplary image.
Unsupervised Pose Flow Learning for Pose Guided Synthesis
Pose guided synthesis aims to generate a new image in an arbitrary target pose while preserving the appearance details from the source image.
CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping
The Reference-based Super-resolution (RefSR) super-resolves a low-resolution (LR) image given an external high-resolution (HR) reference image, where the reference image and LR image share similar viewpoint but with significant resolution gap x8.
SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis
It takes a set of images and their corresponding camera parameters as input and directly infers the 3D model.
Utilizing High-level Visual Feature for Indoor Shopping Mall Navigation
Towards robust and convenient indoor shopping mall navigation, we propose a novel learning-based scheme to utilize the high-level visual information from the storefront images captured by personal devices of users.
Deep Learning for Surface Material Classification Using Haptic And Visual Information
When a user scratches a hand-held rigid tool across an object surface, an acceleration signal can be captured, which carries relevant information about the surface.
Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation
Finally, the optimization problem enables us to take advantage of state-of-the-art fully convolutional network structure for the implementation of the above encoders and decoder.
