Video Reconstruction
35 papers with code • 9 benchmarks • 8 datasets
Source: Deep-SloMo
Benchmarks
These leaderboards are used to track progress in Video Reconstruction
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VoxCeleb1
Event-Camera Dataset
MVSEC
MGif
TED-talks
Tai-Chi-HD
SEN12MS-CR-TS
Videezy4K
Latest papers with no code
Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution
Technically, SATeCo freezes all the parameters of the pre-trained UNet and VAE, and only optimizes two deliberately-designed spatial feature adaptation (SFA) and temporal feature alignment (TFA) modules, in the decoder of UNet and VAE.
EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition
To this end, we propose a novel framework, dubbed EventDance for this unsupervised source-free cross-modal adaptation problem.
Enhanced Event-Based Video Reconstruction with Motion Compensation
To address this, we propose warping the input intensity frames and sparse codes to enhance reconstruction quality.
HDRFlow: Real-Time HDR Video Reconstruction with Large Motions
HDRFlow has three novel designs: an HDR-domain alignment loss (HALoss), an efficient flow network with a multi-size large kernel (MLK), and a new HDR flow training scheme.
Place Anything into Any Video
This paper introduces a novel and efficient system named Place-Anything, which facilitates the insertion of any object into any video solely based on a picture or text description of the target object or element.
Hybrid Video Diffusion Models with 2D Triplane and 3D Wavelet Representation
Generating high-quality videos that synthesize desired realistic content is a challenging task due to their intricate high-dimensionality and complexity of videos.
EventAid: Benchmarking Event-aided Image/Video Enhancement Algorithms with Real-captured Hybrid Dataset
Event cameras are emerging imaging technology that offers advantages over conventional frame-based imaging sensors in dynamic range and sensing speed.
Animatable Virtual Humans: Learning pose-dependent human representations in UV space for interactive performance synthesis
We propose a novel representation of virtual humans for highly realistic real-time animation and rendering in 3D applications.
BASED: Bundle-Adjusting Surgical Endoscopic Dynamic Video Reconstruction using Neural Radiance Fields
We demonstrate this approach on endoscopic surgical scenes from robotic surgery.
Mapping EEG Signals to Visual Stimuli: A Deep Learning Approach to Match vs. Mismatch Classification
Existing approaches to modeling associations between visual stimuli and brain responses are facing difficulties in handling between-subject variance and model generalization.
