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Xiangyang Ji

6 papers hereh-index 695 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author5

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG2
same name
  • Xiangyang Ji — 37 papers, h 45
  • Xiangyang Ji — 19 papers, h 7
  • Xiangyang Ji — 14 papers, h 10
  • Xiangyang Ji — 12 papers, h 3
  • Xiangyang Ji — 9 papers, h 17
  • Xiangyang Ji — 9 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedUnveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios

1 citations · 1 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

Mesh Denoising Transformer

Wenbo Zhao, Xianming Liu, Deming Zhai +2

Mesh denoising, aimed at removing noise from input meshes while preserving their feature structures, is a practical yet challenging task. Despite the remarkable progress in learnin…

cs.CV2024★ 1 cited

SGCNeRF: Few-Shot Neural Rendering via Sparse Geometric Consistency Guidance

Yuru Xiao, Xianming Liu, Deming Zhai +3

Neural Radiance Field (NeRF) technology has made significant strides in creating novel viewpoints. However, its effectiveness is hampered when working with sparsely available views…

cs.CV2024★ 1 cited

Unveiling the Depths: A Multi-Modal Fusion Framework for Challenging Scenarios

Jialei Xu, Xianming Liu, Junjun Jiang +4

Monocular depth estimation from RGB images plays a pivotal role in 3D vision. However, its accuracy can deteriorate in challenging environments such as nighttime or adverse weather…

cs.CV2024

Enhancing Consistency and Mitigating Bias: A Data Replay Approach for Incremental Learning

Chenyang Wang, Junjun Jiang, Xingyu Hu +2

Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, as old data from previous tasks is unavailable when learning a new task. To addre…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.