Media Summary: Authors: Le Yang, Yizeng Han, Xi Chen, Shiji Song, Jifeng Dai, Gao Huang Description: Authors: Anne S. Wannenwetsch, Stefan Roth Description: Encoder-decoder Authors: Zhewei Huang; Ailin Huang; Xiaotao Hu; Chen Hu; Jun Xu; Shuchang Zhou Description: The Space-Time Video ...

Resolution Adaptive Networks For Efficient - Detailed Analysis & Overview

Authors: Le Yang, Yizeng Han, Xi Chen, Shiji Song, Jifeng Dai, Gao Huang Description: Authors: Anne S. Wannenwetsch, Stefan Roth Description: Encoder-decoder Authors: Zhewei Huang; Ailin Huang; Xiaotao Hu; Chen Hu; Jun Xu; Shuchang Zhou Description: The Space-Time Video ... ... framework makes this process extremely faster by introducing an Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ... Authors: Kim, Youngrae; Lim, Jinsu; Cho, Hoonhee*; Lee, Minji; Lee, Dongman; Yoon, Kuk-Jin; Choi, Ho-Jin Description: ...

Kinetica, NVIDIA, and Dell combine powerful analytics, AI acceleration, and robust infrastructure to revolutionize Authors: Zejiang Hou (Princeton University)*; Sun-Yuan Kung (Princeton University) Description: Modern single image ... In this AI Research Roundup episode, Alex discusses the paper: 'Forget Superresolution, Sample Adaptively (when Path Tracing)' ... Don't miss out! Join us at our next KubeCon + CloudNativeCon events in Mumbai, India (18-19 June, 2026), Yokohama, Japan ... We present a new, high‐quality compositing pipeline and navigation approach for variable

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Resolution Adaptive Networks for Efficient Inference
Probabilistic Pixel-Adaptive Refinement Networks
Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution
781 - DynaVSR: Dynamic Adaptive Blind Video Super-Resolution
Residual Feature Aggregation Network for Image Super-Resolution
Efficient Reference-based Video Super-Resolution (ERVSR): Single Reference Image Is All You Need
Network troubleshooting and analysis with Kinetica, NVIDIA and Dell
Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution
Adaptive Sampling for Realistic Path Tracing
tinyML Asia 2021 Video Poster: Efficient inference of low-resolution optic flow on low power...
Paper ID 60 - Propagating Difference Flows for Efficient Video Super-Resolution
Route, Serve, Adapt, Repeat: Adaptive Routing for AI Inference Workl... Nir Rozenbaum & Kellen Swain
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Resolution Adaptive Networks for Efficient Inference

Resolution Adaptive Networks for Efficient Inference

Authors: Le Yang, Yizeng Han, Xi Chen, Shiji Song, Jifeng Dai, Gao Huang Description:

Probabilistic Pixel-Adaptive Refinement Networks

Probabilistic Pixel-Adaptive Refinement Networks

Authors: Anne S. Wannenwetsch, Stefan Roth Description: Encoder-decoder

Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

Authors: Zhewei Huang; Ailin Huang; Xiaotao Hu; Chen Hu; Jun Xu; Shuchang Zhou Description: The Space-Time Video ...

781 - DynaVSR: Dynamic Adaptive Blind Video Super-Resolution

781 - DynaVSR: Dynamic Adaptive Blind Video Super-Resolution

... framework makes this process extremely faster by introducing an

Residual Feature Aggregation Network for Image Super-Resolution

Residual Feature Aggregation Network for Image Super-Resolution

Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ...

Efficient Reference-based Video Super-Resolution (ERVSR): Single Reference Image Is All You Need

Efficient Reference-based Video Super-Resolution (ERVSR): Single Reference Image Is All You Need

Authors: Kim, Youngrae; Lim, Jinsu; Cho, Hoonhee*; Lee, Minji; Lee, Dongman; Yoon, Kuk-Jin; Choi, Ho-Jin Description: ...

Network troubleshooting and analysis with Kinetica, NVIDIA and Dell

Network troubleshooting and analysis with Kinetica, NVIDIA and Dell

Kinetica, NVIDIA, and Dell combine powerful analytics, AI acceleration, and robust infrastructure to revolutionize

Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution

Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution

Authors: Zejiang Hou (Princeton University)*; Sun-Yuan Kung (Princeton University) Description: Modern single image ...

Adaptive Sampling for Realistic Path Tracing

Adaptive Sampling for Realistic Path Tracing

In this AI Research Roundup episode, Alex discusses the paper: 'Forget Superresolution, Sample Adaptively (when Path Tracing)' ...

tinyML Asia 2021 Video Poster: Efficient inference of low-resolution optic flow on low power...

tinyML Asia 2021 Video Poster: Efficient inference of low-resolution optic flow on low power...

tinyML Asia 2021

Paper ID 60 - Propagating Difference Flows for Efficient Video Super-Resolution

Paper ID 60 - Propagating Difference Flows for Efficient Video Super-Resolution

Propagating Difference Flows for

Route, Serve, Adapt, Repeat: Adaptive Routing for AI Inference Workl... Nir Rozenbaum & Kellen Swain

Route, Serve, Adapt, Repeat: Adaptive Routing for AI Inference Workl... Nir Rozenbaum & Kellen Swain

Don't miss out! Join us at our next KubeCon + CloudNativeCon events in Mumbai, India (18-19 June, 2026), Yokohama, Japan ...

Adaptive Compositing and Navigation of Variable Resolution Images | Eurographics'2021 Full Paper

Adaptive Compositing and Navigation of Variable Resolution Images | Eurographics'2021 Full Paper

We present a new, high‐quality compositing pipeline and navigation approach for variable