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ElasticFormer: Detecting Objects in HRW Shots via Elastic Computing Vision Transformer

Paper recorded by Signals 4 on 2026-10-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CV · 计算机视觉 · first seen 2026-10-30

Abstract

Recent advances in gigapixel-level imaging have brought High-Resolution Wide shots to the forefront of research. However, these images present significant challenges: extreme sparsity of foreground, gigapixel-level resolutions and diverse target counts. This makes traditional close-up detectors inaccurate and slow as they are overwhelmed by the background. Although previous research has explored s

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#70 most recent of 710 cs.CV papers we have recorded · ↑ newer: UniRA: Unified Representation Alignment and Auto-Encoding for Efficien · ↓ older: BiHashFormer: Hash-Driven Dual-Branch Transformer for Efficient Object
Cite this page: ElasticFormer: Detecting Objects in HRW Shots via Elastic Computing Vision Transformer: the #70 most recent of 710 cs.CV papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/elasticformer-detecting-objects-in-hrw-shots-via-elastic-computing-vision-transf.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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