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Found 33 papers, 13 papers with code
LPSNet: End-to-End Human Pose and Shape Estimation with Lensless Imaging
Human pose and shape (HPS) estimation with lensless imaging is not only beneficial to privacy protection but also can be used in covert surveillance scenarios due to the small size and simple structure of this device.
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusion
In the second stage, we integrate a degradation-aware module into a simplified ControlNet, enabling flexible adaptation to various degradations based on the learned representations.
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic.
Ranked #1 on
Facial Action Unit Detection
on DISFA
A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet closely-related computer vision tasks widely studied during the past decades.
KeDuSR: Real-World Dual-Lens Super-Resolution via Kernel-Free Matching
Different from them, we propose to first align the Ref with the center region (namely the overlapped FoV area) of the LR input by combining global warping and local warping to make the aligned Ref be sharp and consistent.
Learning to See Low-Light Images via Feature Domain Adaptation
To solve this problem, we propose a single-stage network empowered by Feature Domain Adaptation (FDA) to decouple the denoising and color mapping tasks in raw LLIE.
MARIS: Referring Image Segmentation via Mutual-Aware Attention Features
Referring image segmentation (RIS) aims to segment a particular region based on a language expression prompt.
High-Quality Animatable Dynamic Garment Reconstruction from Monocular Videos
To alleviate the ambiguity estimating 3D garments from monocular videos, we design a multi-hypothesis deformation module that learns spatial representations of multiple plausible deformations.
Recaptured Raw Screen Image and Video Demoiréing via Channel and Spatial Modulations
The spatial modulation utilizes the feature with large receptive field to modulate the feature with small receptive field.
Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
Anatomically, there are innumerable correlations between AUs, which contain rich information and are vital for AU detection.
Ranked #2 on
Facial Action Unit Detection
on DISFA
Joint Denoising and Fusion with Short- and Long-exposure Raw Pairs
Current methods predominantly generate HDR images from a set of bracketed exposure sRGB images.
rPPG-MAE: Self-supervised Pre-training with Masked Autoencoders for Remote Physiological Measurement
However, they focus on the contrastive learning between samples, which neglect the inherent self-similar prior in physiological signals and seem to have a limited ability to cope with noisy.
Physics-Informed Ensemble Representation for Light-Field Image Super-Resolution
Recent learning-based approaches have achieved significant progress in light field (LF) image super-resolution (SR) by exploring convolution-based or transformer-based network structures.
NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigation
They are complementary -- the outer navigation is to identify global-view semantic directions, and the inner refinement dedicates to fine-grained attributes.
HDR Video Reconstruction with a Large Dynamic Dataset in Raw and sRGB Domains
Based on this dataset, we further propose a Raw-HDRNet, which utilizes the raw LDR frames as inputs.
Unsupervised HDR Image and Video Tone Mapping via Contrastive Learning
We construct a large-scale unpaired HDR-LDR video dataset to facilitate the unsupervised training process for video tone mapping.
Dec-Adapter: Exploring Efficient Decoder-Side Adapter for Bridging Screen Content and Natural Image Compression
Therefore, we propose a Dec-Adapter, a pioneering entropy-efficient transfer learning module for the decoder to bridge natural image and screen content compression.
Learning Semantic-Aware Disentangled Representation for Flexible 3D Human Body Editing
3D human body representation learning has received increasing attention in recent years.
ITSRN++: Stronger and Better Implicit Transformer Network for Continuous Screen Content Image Super-Resolution
Specifically, we propose a modulation based transformer as the upsampler, which modulates the pixel features in discrete space via a periodic nonlinear function to generate features for continuous pixels.
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Dataset
Our code and dataset are available at https://github. com/zmzhang1998/Real-RawVSR.
FOF: Learning Fourier Occupancy Field for Monocular Real-time Human Reconstruction
Based on FOF, we design the first 30+FPS high-fidelity real-time monocular human reconstruction framework.
Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic Segmentation
The perturbations for unlabeled data enable the consistency training loss, which benefits semi-supervised semantic segmentation.
Implicit Transformer Network for Screen Content Image Continuous Super-Resolution
Nowadays, there is an explosive growth of screen contents due to the wide application of screen sharing, remote cooperation, and online education.
Spatio-temporal Contrastive Domain Adaptation for Action Recognition
Unsupervised domain adaptation (UDA) for human action recognition is a practical and challenging problem.
PISE: Person Image Synthesis and Editing with Decoupled GAN
The results of qualitative and quantitative experiments demonstrate the superiority of our model on human pose transfer.
Supervised Raw Video Denoising with a Benchmark Dataset on Dynamic Scenes
Clean video frames for dynamic scenes cannot be captured with a long-exposure shutter or averaging multi-shots as was done for static images.
STC-Flow: Spatio-temporal Context-aware Optical Flow Estimation
In this paper, we propose a spatio-temporal contextual network, STC-Flow, for optical flow estimation.
FPCR-Net: Feature Pyramidal Correlation and Residual Reconstruction for Optical Flow Estimation
To exploit such flexible and comprehensive information, we propose a semi-supervised Feature Pyramidal Correlation and Residual Reconstruction Network (FPCR-Net) for optical flow estimation from frame pairs.
Learning to Reconstruct and Understand Indoor Scenes from Sparse Views
This paper proposes a new method for simultaneous 3D reconstruction and semantic segmentation of indoor scenes.
Temporal-Spatial Mapping for Action Recognition
We propose a video level 2D feature representation by transforming the convolutional features of all frames to a 2D feature map, referred to as VideoMap.
Ranked #51 on
Action Recognition
on UCF101
Robust Non-Rigid Registration with Reweighted Position and Transformation Sparsity
Non-rigid registration is challenging because it is ill-posed with high degrees of freedom and is thus sensitive to noise and outliers.
CID: Combined Image Denoising in Spatial and Frequency Domains Using Web Images
Second, to handle heavy noise, we further propose using the denoising image to improve image registration of the retrieved Web images, 3D cube building, and the estimation of filtering parameters in the frequency domain.
