activity
20192026
most citedAMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation

201 citations · 281 across the 12 of their papers we have counts for

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8 papers · 1 filter

cs.CV2024

CompGS: Unleashing 2D Compositionality for Compositional Text-to-3D via Dynamically Optimizing 3D Gaussians

Chongjian Ge, Chenfeng Xu, Yuanfeng Ji +6

Recent breakthroughs in text-guided image generation have significantly advanced the field of 3D generation. While generating a single high-quality 3D object is now feasible, gener…

cs.CV2023

Large Language Models as Automated Aligners for benchmarking Vision-Language Models

Yuanfeng Ji, Chongjian Ge, Weikai Kong +4

With the advancements in Large Language Models (LLMs), Vision-Language Models (VLMs) have reached a new level of sophistication, showing notable competence in executing intricate c…

cs.CV2023★ 35 cited

MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

Jianning Li, Zongwei Zhou, Jiancheng Yang +154

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…

cs.CV2023★ 5 cited

DDP: Diffusion Model for Dense Visual Prediction

Yuanfeng Ji, Zhe Chen, Enze Xie +6

We propose a simple, efficient, yet powerful framework for dense visual predictions based on the conditional diffusion pipeline. Our approach follows a "noise-to-map" generative pa…

cs.CV2021★ 1 cited

Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation

Lingyun Wu, Zhiqiang Hu, Yuanfeng Ji +2

Precise localization of polyp is crucial for early cancer screening in gastrointestinal endoscopy. Videos given by endoscopy bring both richer contextual information as well as mor…

cs.CV2021★ 15 cited

Multi-Compound Transformer for Accurate Biomedical Image Segmentation

Yuanfeng Ji, Ruimao Zhang, Huijie Wang +4

The recent vision transformer(i.e.for image classification) learns non-local attentive interaction of different patch tokens. However, prior arts miss learning the cross-scale depe…