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Lingyu Kong

Tsinghua University, Microsoft Research

5 papers hereh-index 334 citations5 works total

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

author position
  • first author1
  • middle author4

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

fields
  • cs.CV4
  • cs.AI1
affiliations
  • Tsinghua University, Microsoft Research
ORCID 0009-0004-5222-3502
same name
  • Lingyu Kong — 6 papers, h 7
  • Lingyu Kong — 4 papers, h 2
  • Lingyu Kong — 2 papers, h 5
  • Lingyu Kong — 1 paper, h 13
  • Lingyu Kong — 1 paper
  • Lingyu Kong — 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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement

Lingyu Kong, Ruicheng Li, Ruicheng Wang +4

Monocular geometry estimation has recently achieved impressive performance across diverse scenes. However, state-of-the-art models still face notable distortion in local 3D structu…

cs.CV2026

IDEAL: In-DEpth ALignment Makes A Discrete Representation AutoEncoder

Yitong Chen, Zijie Diao, Junke Wang +5

Built on pretrained vision foundation models (VFMs), representation autoencoders (RAEs) have recently emerged as a promising approach for constructing semantically rich latent spac…

cs.CV2025

Pix2Cap-COCO: Advancing Visual Comprehension via Pixel-Level Captioning

Zuyao You, Junke Wang, Lingyu Kong +2

We present Pix2Cap-COCO, the first panoptic pixel-level caption dataset designed to advance fine-grained visual understanding. To achieve this, we carefully design an automated ann…

cs.CV2025

FOCUS: Towards Universal Foreground Segmentation

Zuyao You, Lingyu Kong, Lingchen Meng +1

Foreground segmentation is a fundamental task in computer vision, encompassing various subdivision tasks. Previous research has typically designed task-specific architectures for e…

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