Search Results for author:
Found 23 papers, 8 papers with code
IA2U: A Transfer Plugin with Multi-Prior for In-Air Model to Underwater
In underwater environments, variations in suspended particle concentration and turbidity cause severe image degradation, posing significant challenges to image enhancement (IE) and object detection (OD) tasks.
FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking
Then, we instruct-tune an open-sourced language model, called LLaMA, using this evidence, enabling it to predict the veracity of the input claim more accurately.
AGTGAN: Unpaired Image Translation for Photographic Ancient Character Generation
We evaluate our approach on the photographic ancient character datasets, e. g., OBC306 and CSDD.
Deep Learning Methods for Calibrated Photometric Stereo and Beyond
We summarize the performance of deep learning photometric stereo models on the most widely-used benchmark data set.
Restoration of User Videos Shared on Social Media
This paper presents a new general video restoration framework for the restoration of user videos shared on social media platforms.
Deep Progressive Feature Aggregation Network for High Dynamic Range Imaging
The primary challenges are ghosting artifacts caused by object motion between low dynamic range images and distorted content in under and overexposed regions.
Online Video Super-Resolution with Convolutional Kernel Bypass Graft
Then, our proposed CKBG method enhances this lightweight base model by bypassing the original network with ``kernel grafts'', which are extra convolutional kernels containing the prior knowledge of external pretrained image SR models.
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor.
A Hybrid Egocentric Activity Anticipation Framework via Memory-Augmented Recurrent and One-Shot Representation Forecasting
Furthermore, to resolve the limitation (ii), a one-shot transferring paradigm is proposed to enrich the forecasted representations, by distilling the holistic activity semantics after the target anticipation moment, in the offline training.
Progressive and Selective Fusion Network for High Dynamic Range Imaging
We propose a novel method that can better fuse the features based on two ideas.
Enhancing and Learning Denoiser without Clean Reference
Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks.
Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing
Multi-task learning is an effective learning strategy for deep-learning-based facial expression recognition tasks.
Facial Expression Recognition
Facial Expression Recognition (FER)
+2
Enhancement of a CNN-Based Denoiser Based on Spatial and Spectral Analysis
Since most of the content or energy of natural images resides in the low-frequency spectrum, their transformed coefficients in the frequency domain are highly imbalanced.
Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection
This paper proposes a fast video salient object detection model, based on a novel recurrent network architecture, named Pyramid Dilated Bidirectional ConvLSTM (PDB-ConvLSTM).
Ranked #1 on
Video Salient Object Detection
on UVSD
(using extra training data)
Soft Locality Preserving Map (SLPM) for Facial Expression Recognition
Furthermore, the proposed feature-generation method can improve the generalizability of the underlying manifolds for facial expression recognition.
Image Super-resolution via Feature-augmented Random Forest
In this paper, we present a novel feature-augmented random forest (FARF) for image super-resolution, where the conventional gradient-based features are augmented with gradient magnitudes and different feature recipes are formulated on different stages in an RF.
Ranked #48 on
Image Super-Resolution
on BSD100 - 4x upscaling
Joint Maximum Purity Forest with Application to Image Super-Resolution
In the JMPF scheme, the original feature space is transformed into a compactly pre-clustered feature space, via a trained rotation matrix.
Ranked #50 on
Image Super-Resolution
on BSD100 - 4x upscaling
Cascade one-vs-rest detection network for fine-grained recognition without part annotations
To bridge this gap, we introduce a cascaded structure to eliminate background and exploit a one-vs-rest loss to capture more minute variances among different subordinate categories.
Efficient Likelihood Bayesian Constrained Local Model
The constrained local model (CLM) proposes a paradigm that the locations of a set of local landmark detectors are constrained to lie in a subspace, spanned by a shape point distribution model (PDM).
Person Re-Identification by Unsupervised Video Matching
Crucially, this model does not require pairwise labelled training data (i. e. unsupervised) therefore readily scalable to large scale camera networks of arbitrary camera pairs without the need for exhaustive data annotation for every camera pair.
Cascaded Face Alignment via Intimacy Definition Feature
In this paper, we present a random-forest based fast cascaded regression model for face alignment, via a novel local feature.
A Local Active Contour Model for Image Segmentation with Intensity Inhomogeneity
The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field with the original signal within the window.
