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Qi Wang

5 papers hereh-index 274 citations9 works total

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

author position
  • middle author2
  • last author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Qi Wang — 16 papers, h 5
  • Qi Wang — 16 papers, h 7
  • Qi Wang — 10 papers, h 4
  • Qi Wang — 9 papers, h 7
  • Qi Wang — 9 papers, h 5
  • Qi Wang — 8 papers, 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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

STAR-IOD: Scale-decoupled Topology Alignment with Pseudo-label Refinement for Remote Sensing Incremental Object Detection

Yaoteng Zhang, Qing Zhou, Junyu Gao +1

Remote sensing imagery typically arrives in the form of continuous data streams. Traditional detectors often forget previously learned categories when learning new ones; therefore,…

cs.CV2026

Discriminative Perception via Anchored Description for Reasoning Segmentation

Tao Yang, Qing Zhou, Yanliang Li +1

Reasoning segmentation increasingly employs reinforcement learning to generate explanatory reasoning chains that guide Multimodal Large Language Models. While these geometric rewar…

cs.CV2026

Beyond Prompt Degradation: Prototype-guided Dual-pool Prompting for Incremental Object Detection

Yaoteng Zhang, Zhou Qing, Junyu Gao +1

Incremental Object Detection (IOD) aims to continuously learn new object categories without forgetting previously learned ones. Recently, prompt-based methods have gained popularit…

cs.CV2024

STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery

Yansheng Li, Linlin Wang, Tingzhu Wang +11

Scene graph generation (SGG) in satellite imagery (SAI) benefits promoting understanding of geospatial scenarios from perception to cognition. In SAI, objects exhibit great variati…

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