activity
20242026
most citedPolypSegTrack: Unified Foundation Model for Colonoscopy Video Analysis

1 citations · 1 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV2026

SPOT: Contrast-Driven Face Occlusion Segmentation via Self-Supervised Prompt Learning

Lingsong Wang, Mancheng Meng, Ziyan Wu +3

Existing face parsing methods usually misclassify occlusions as facial components. This is because occlusion is a high-level concept, it does not refer to a concrete category of ob…

cs.CV2025

Consistent Instance Field for Dynamic Scene Understanding

Junyi Wu, Van Nguyen Nguyen, Benjamin Planche +11

We introduce Consistent Instance Field, a continuous and probabilistic spatio-temporal representation for dynamic scene understanding. Unlike prior methods that rely on discrete tr…

cs.CV20251 cited

PolypSegTrack: Unified Foundation Model for Colonoscopy Video Analysis

Anwesa Choudhuri, Zhongpai Gao, Meng Zheng +3

Early detection, accurate segmentation, classification and tracking of polyps during colonoscopy are critical for preventing colorectal cancer. Many existing deep-learning-based me…

cs.CV2025

7DGS: Unified Spatial-Temporal-Angular Gaussian Splatting

Zhongpai Gao, Benjamin Planche, Meng Zheng +3

Real-time rendering of dynamic scenes with view-dependent effects remains a fundamental challenge in computer graphics. While recent advances in Gaussian Splatting have shown promi…

cs.CV2025

Anatomy-Aware Conditional Image-Text Retrieval

Meng Zheng, Jiajin Zhang, Benjamin Planche +3

Image-Text Retrieval (ITR) finds broad applications in healthcare, aiding clinicians and radiologists by automatically retrieving relevant patient cases in the database given the q…

cs.CV2025

CHROME: Clothed Human Reconstruction with Occlusion-Resilience and Multiview-Consistency from a Single Image

Arindam Dutta, Meng Zheng, Zhongpai Gao +5

Reconstructing clothed humans from a single image is a fundamental task in computer vision with wide-ranging applications. Although existing monocular clothed human reconstruction…