Xiang Ji (纪祥)

I am a postdoc researcher in Next Generation Artificial Intelligence Research Center at Graduate School of Information Science and Technology (IST), The University of Tokyo , supervised by Professor Yinqiang Zheng.

My research interests include computational imaging and generative AI.

Email: ji-xiang [at] ynl.t.u-tokyo.ac.jp

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We present a new task of HDR photosequencing

we present RS NeRF, a method designed to synthesize normal images from novel views using input with RS distortions.

We proposed a novel cross-shutter setting for motion decomposition of a single blurry image, inspired by the complementary exposure characteristics of GS and RS cameras.

We highlighted the effects of shutter mode induced degradations on the VFI task and proposed a generic model to interpolate middle clear frames at arbitrary times

In this paper, we explore a novel in-between exposure mode, called global reset release (GRR) shutter, and propose a residual spatially-compensated and spectrally-enhanced Transformer (RSS-T) block for row-dependent deblurring of a single GRR image.

We propose a blur interpolation transformer (BiT) to effectively unravel the underlying temporal correlation encoded in blur.

This paper first attempts to restore clean GS videos from the RS sensor with the widely ignored global reset feature.

We present InferWiki, a Knowledge Graph Completion (KGC)dataset that improves upon existing benchmarks in inferential ability, assumptions, and patterns.

• Advisor: Prof. Yinqiang Zheng

• Advisor: Prof. Yixin Cao and Hanwang Zhang