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Ruibo Li

14 papers hereh-index 10480 citations22 works total

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

author position
  • first author4
  • middle author10

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.RO1
same name
  • Ruibo Li — 5 papers, h 4
  • Ruibo Li — 4 papers, h 2
  • Ruibo Li — 2 papers
  • Ruibo Li — 1 paper, h 3
  • Ruibo Li — 1 paper, h 2
  • Ruibo Li — 1 paper, h 1

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
20212026
most citedEfficient Few-Shot Object Detection via Knowledge Inheritance

53 citations · 69 across the 12 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CV2025

IC-World: In-Context Generation for Shared World Modeling

Fan Wu, Jiacheng Wei, Ruibo Li +4

Video-based world models have recently garnered increasing attention for their ability to synthesize diverse and dynamic visual environments. In this paper, we focus on shared worl…

cs.CV2025★ 1 cited

Weakly and Self-Supervised Class-Agnostic Motion Prediction for Autonomous Driving

Ruibo Li, Hanyu Shi, Zhe Wang +1

Understanding motion in dynamic environments is critical for autonomous driving, thereby motivating research on class-agnostic motion prediction. In this work, we investigate weakl…

cs.CV2025

DSOcc: Leveraging Depth Awareness and Semantic Aid to Boost Camera-Based 3D Semantic Occupancy Prediction

Naiyu Fang, Zheyuan Zhou, Kang Wang +5

Camera-based 3D semantic occupancy prediction offers an efficient and cost-effective solution for perceiving surrounding scenes in autonomous driving. However, existing works rely…

cs.CV2025

TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion

Yiran Wang, Jiaqi Li, Chaoyi Hong +6

Radar-Camera depth estimation aims to predict dense and accurate metric depth by fusing input images and Radar data. Model efficiency is crucial for this task in pursuit of real-ti…

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