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Mengcheng Lan

16 papers hereh-index 9405 citations19 works total

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

author position
  • first author5
  • middle author10

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG4
  • cs.AI1
  • eess.IV1
  • q-bio.NC1
same name
  • Mengcheng Lan — 3 papers, h 7

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
20232026
most citedSmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation

3 citations · 8 across the 15 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

4 papers · 2 filters

cs.CV2024★ 2 cited

GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding

Yue Zhou, Mengcheng Lan, Xiang Li +6

Remote sensing (RS) visual grounding aims to use natural language expression to locate specific objects (in the form of the bounding box or segmentation mask) in RS images, enhanci…

cs.CV2024

Text4Seg: Reimagining Image Segmentation as Text Generation

Mengcheng Lan, Chaofeng Chen, Yue Zhou +5

Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks; however, effectively integrating image segmentation into these models remains…

cs.CV2024

ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels. While Contrastive Language-Image Pre-tra…

cs.CV2024

ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains cha…

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