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Found 14 papers, 5 papers with code
VI3DRM:Towards meticulous 3D Reconstruction from Sparse Views via Photo-Realistic Novel View Synthesis
Recently, methods like Zero-1-2-3 have focused on single-view based 3D reconstruction and have achieved remarkable success.
VividPose: Advancing Stable Video Diffusion for Realistic Human Image Animation
This enables accurate alignment of pose and shape in the generated videos, providing a robust framework capable of handling a wide range of body shapes and dynamic hand movements.
SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformer
Point cloud completion has become increasingly popular among generation tasks of 3D point clouds, as it is a challenging yet indispensable problem to recover the complete shape of a 3D object from its partial observation.
Ranked #7 on
Point Cloud Completion
on Completion3D
Learning To Memorize Feature Hallucination for One-Shot Image Generation
In this paper, we propose a novel model to explicitly learn and memorize reusable features that can help hallucinate novel category images.
Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake Videos
In addition, we designed a tool called Localizator to compare the difference between the original traced video and the fake video.
Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution
In this paper, we propose a novel blind SR framework to super-resolve LR images degraded by arbitrary blur kernel with accurate kernel estimation in frequency domain.
Frequency Consistent Adaptation for Real World Super Resolution
From this point of view, we design a novel Frequency Consistent Adaptation (FCA) that ensures the frequency domain consistency when applying existing SR methods to the real scene.
SLCRF: Subspace Learning with Conditional Random Field for Hyperspectral Image Classification
In SLCRF, first, the 3D convolutional autoencoder (3DCAE) is introduced to remove the redundant information in HSI pixels.
DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval
With a small number of labeled samples for training, it can save considerable manpower and material resources, especially when the amount of high spatial resolution remote sensing images (HSR-RSIs) increases considerably.
Real-World Super-Resolution via Kernel Estimation and Noise Injection
Recent state-of-the-art super-resolution methods have achieved impressive performance on ideal datasets regardless of blur and noise.
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
This paper reviews the NTIRE 2020 challenge on real world super-resolution.
Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution
Constrained image splicing detection and localization (CISDL) is a newly proposed challenging task for image forensics, which investigates two input suspected images and identifies whether one image has suspected regions pasted from the other.
Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks
In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images.
Unsupervised Diverse Colorization via Generative Adversarial Networks
Colorization of grayscale images has been a hot topic in computer vision.
