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Yilun Zhang

4 papers hereh-index 489 citations7 works total

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Yilun Zhang — 4 papers, h 3
  • Yilun Zhang — 2 papers, h 2
  • Yilun Zhang — 2 papers, h 3
  • Yilun Zhang — 1 paper, h 3
  • Yilun Zhang — 1 paper, h 2

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
20182023
most citedDFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance

14 citations · 25 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023

On the Importance of Spatial Relations for Few-shot Action Recognition

Yilun Zhang, Yuqian Fu, Xingjun Ma +4

Deep learning has achieved great success in video recognition, yet still struggles to recognize novel actions when faced with only a few examples. To tackle this challenge, few-sho…

cs.CV2021★ 6 cited

A real-time spatiotemporal AI model analyzes skill in open surgical videos

Emmett D. Goodman, Krishna K. Patel, Yilun Zhang +10

Open procedures represent the dominant form of surgery worldwide. Artificial intelligence (AI) has the potential to optimize surgical practice and improve patient outcomes, but eff…

cs.CV2019★ 14 cited

DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance

Yilun Zhang, Ty Nguyen, Ian D. Miller +4

Depth estimation is an important capability for autonomous vehicles to understand and reconstruct 3D environments as well as avoid obstacles during the execution. Accurate depth se…

cs.CV2018★ 5 cited

Multiview Supervision By Registration

Yilun Zhang, Hyun Soo Park

This paper presents a semi-supervised learning framework to train a keypoint detector using multiview image streams given the limited labeled data (typically <4\%). We leverage t…

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