HyperAI
HyperAI
الرئيسية
المنصة
الوثائق
الأخبار
الأوراق البحثية
الدروس
مجموعات البيانات
الموسوعة
SOTA
نماذج LLM
لوحة الأداء GPU
الفعاليات
البحث
حول
شروط الخدمة
سياسة الخصوصية
العربية
HyperAI
HyperAI
Toggle Sidebar
البحث في الموقع...
⌘
K
Command Palette
Search for a command to run...
المنصة
الرئيسية
SOTA
الفيديو فائق الدقة
Video Super Resolution On Vid4 4X Upscaling
Video Super Resolution On Vid4 4X Upscaling
المقاييس
PSNR
SSIM
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
PSNR
SSIM
Paper Title
EvTexture+
29.78
0.8983
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
EvTexture
29.51
0.8909
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
IART
28.26
0.8517
Enhancing Video Super-Resolution via Implicit Resampling-based Alignment
MIA-VSR
28.20
0.8507
Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
CFD-PSRT
28.18
0.8503
Collaborative Feedback Discriminative Propagation for Video Super-Resolution
PSRT-recurrent
28.07
0.8485
Rethinking Alignment in Video Super-Resolution Transformers
RVRT
27.99
0.8462
Recurrent Video Restoration Transformer with Guided Deformable Attention
VRT
27.93
0.8425
VRT: A Video Restoration Transformer
BasicVSR++
27.79
0.8400
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
SATeCo
27.44
0.8420
Learning Spatial Adaptation and Temporal Coherence in Diffusion Models for Video Super-Resolution
IconVSR
27.39
0.8279
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
EDVR
27.35
0.8264
EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
VSR-DUF
27.33
0.8319
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
BasicVSR
27.24
0.8251
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
RBPN/6-PF
27.12
0.8180
Recurrent Back-Projection Network for Video Super-Resolution
VideoGigaGAN
27.04
-
VideoGigaGAN: Towards Detail-rich Video Super-Resolution
SOF-VSR
26.01
0.771
Learning for Video Super-Resolution through HR Optical Flow Estimation
SOF-VSR
26
0.772
Deep Video Super-Resolution using HR Optical Flow Estimation
TecoGAN⊖
25.89
-
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
DRDVSR
25.88
0.774
Detail-revealing Deep Video Super-resolution
0 of 27 row(s) selected.
Previous
Next
Video Super Resolution On Vid4 4X Upscaling | SOTA | HyperAI