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20162022
most citedRevisiting RCAN: Improved Training for Image Super-Resolution

47 citations · 160 across the 11 of their papers we have counts for

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23 papers · 1 filter

cs.CV202238 cited

SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections

Mark Boss, Andreas Engelhardt, Abhishek Kar +5

Inverse rendering of an object under entirely unknown capture conditions is a fundamental challenge in computer vision and graphics. Neural approaches such as NeRF have achieved ph…

cs.CV202211 cited

An Extendable, Efficient and Effective Transformer-based Object Detector

Hwanjun Song, Deqing Sun, Sanghyuk Chun +5

Transformers have been widely used in numerous vision problems especially for visual recognition and detection. Detection transformers are the first fully end-to-end learning syste…

cs.CV20225 cited

Kubric: A scalable dataset generator

Klaus Greff, Francois Belletti, Lucas Beyer +32

Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…

cs.CV202247 cited

Revisiting RCAN: Improved Training for Image Super-Resolution

Zudi Lin, Prateek Garg, Atmadeep Banerjee +6

Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight. However, most SR models were optimized with dated training strategies. In this…

cs.CV202121 cited

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation

Gen Li, Varun Jampani, Laura Sevilla-Lara +3

Prototype learning is extensively used for few-shot segmentation. Typically, a single prototype is obtained from the support feature by averaging the global object information. How…

cs.CV2021

LASR: Learning Articulated Shape Reconstruction from a Monocular Video

Gengshan Yang, Deqing Sun, Varun Jampani +6

Remarkable progress has been made in 3D reconstruction of rigid structures from a video or a collection of images. However, it is still challenging to reconstruct nonrigid structur…