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Found 13 papers, 7 papers with code
CoherentGS: Sparse Novel View Synthesis with Coherent 3D Gaussians
The field of 3D reconstruction from images has rapidly evolved in the past few years, first with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian Splatting (3DGS).
ReShader: View-Dependent Highlights for Single Image View-Synthesis
To address this major problem, we make a key observation that the process of synthesizing novel views requires changing the shading of the pixels based on the novel camera, and moving them to appropriate locations.
PhotoMat: A Material Generator Learned from Single Flash Photos
Instead, we train a generator for a neural material representation that is rendered with a learned relighting module to create arbitrarily lit RGB images; these are compared against real photos using a discriminator.
Implicit View-Time Interpolation of Stereo Videos using Multi-Plane Disparities and Non-Uniform Coordinates
In this paper, we propose an approach for view-time interpolation of stereo videos.
3D-Aware Facial Landmark Detection via Multi-View Consistent Training on Synthetic Data
Accurate facial landmark detection on wild images plays an essential role in human-computer interaction, entertainment, and medical applications.
Frame Interpolation for Dynamic Scenes with Implicit Flow Encoding
To do this, we propose to encode the bidirectional flows into a coordinate-based network, powered by a hypernetwork, to obtain a continuous representation of the flow across time.
Multi-Stage Raw Video Denoising with Adversarial Loss and Gradient Mask
We propose to do this by first explicitly aligning the neighboring frames to the current frame using a convolutional neural network (CNN).
Ranked #2 on
Video Denoising
on CRVD
Single Image HDR Reconstruction Using a CNN with Masked Features and Perceptual Loss
Since the number of HDR images for training is limited, we propose to train our system in two stages.
Inverse-Tone-Mapping
Image and Video Processing
Graphics
Deep Slow Motion Video Reconstruction with Hybrid Imaging System
In this paper, we address this problem using two video streams as input; an auxiliary video with high frame rate and low spatial resolution, providing temporal information, in addition to the standard main video with low frame rate and high spatial resolution.
Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
We present a practical and robust deep learning solution for capturing and rendering novel views of complex real world scenes for virtual exploration.
Deep Hybrid Real and Synthetic Training for Intrinsic Decomposition
Experimental results show that our approach produces better results than the state-of-the-art DL and non-DL methods on various synthetic and real datasets both visually and numerically.
Light Field Video Capture Using a Learning-Based Hybrid Imaging System
Given a 3 fps light field sequence and a standard 30 fps 2D video, our system can then generate a full light field video at 30 fps.
Learning-Based View Synthesis for Light Field Cameras
Specifically, we propose a novel learning-based approach to synthesize new views from a sparse set of input views.
