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20222026
most citedMaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation

4 citations · 8 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

CogniMap3D: Cognitive 3D Mapping and Rapid Retrieval

Feiran Wang, Junyi Wu, Dawen Cai +2

We present CogniMap3D, a bioinspired framework for dynamic 3D scene understanding and reconstruction that emulates human cognitive processes. Our approach maintains a persistent me…

cs.CV2025

TraceFlow: Dynamic 3D Reconstruction of Specular Scenes Driven by Ray Tracing

Jiachen Tao, Junyi Wu, Haoxuan Wang +3

We present TraceFlow, a novel framework for high-fidelity rendering of dynamic specular scenes by addressing two key challenges: precise reflection direction estimation and physica…

cs.CV2025★ 1 cited

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation

Bin Xie, Hao Tang, Dawen Cai +2

Segment Anything Model (SAM) has demonstrated impressive zero-shot performance and brought a range of unexplored capabilities to natural image segmentation tasks. However, as a ver…

cs.CV2024★ 4 cited

MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation

Bin Xie, Hao Tang, Bin Duan +3

Segment Anything Model (SAM), a prompt-driven foundation model for natural image segmentation, has demonstrated impressive zero-shot performance. However, SAM does not work when di…

cs.CV2022★ 3 cited

Few-shot Medical Image Segmentation with Cycle-resemblance Attention

Hao Ding, Changchang Sun, Hao Tang +2

Recently, due to the increasing requirements of medical imaging applications and the professional requirements of annotating medical images, few-shot learning has gained increasing…