activity
20202026
most citedAnalysis on DeepLabV3+ Performance for Automatic Steel Defects Detection

6 citations · 11 across the 18 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editing

Junliang Ye, Kenkun Liu, Guocun Wang +13

Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing. However, unified 3D modeling…

cs.CV2026

JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space

Xinnan Zhu, Ruijie Xu, Jiayu Ying +4

Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelines, resulting in high test-time…

cs.CV2026

HY3D-Bench: Generation of 3D Assets

Team Hunyuan3D, :, Bowen Zhang +22

While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlene…

cs.CV2026

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions

Ji Zhou, Yilin Ding, Yongqi Zhao +4

Reliable environmental perception remains one of the main obstacles for safe operation of automated vehicles. Safety of the Intended Functionality (SOTIF) concerns safety risks fro…

cs.CV2025

P3-SAM: Native 3D Part Segmentation

Changfeng Ma, Yang Li, Xinhao Yan +7

Segmenting 3D assets into their constituent parts is crucial for enhancing 3D understanding, facilitating model reuse, and supporting various applications such as part generation.…

cs.CV2022

Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning

Tianyuan Yao, Chang Qu, Jun Long +13

With the rapid development of self-supervised learning (e.g., contrastive learning), the importance of having large-scale images (even without annotations) for training a more gene…

cs.CV2021

Semi-Supervised Contrastive Learning for Remote Sensing: Identifying Ancient Urbanization in the South Central Andes

Jiachen Xu, Junlin Guo, James Zimmer-Dauphinee +7

Archaeology has long faced fundamental issues of sampling and scalar representation. Traditionally, the local-to-regional-scale views of settlement patterns are produced through sy…

cs.CV2021★ 1 cited

Exploring Versatile Prior for Human Motion via Motion Frequency Guidance

Jiachen Xu, Min Wang, Jingyu Gong +4

Prior plays an important role in providing the plausible constraint on human motion. Previous works design motion priors following a variety of paradigms under different circumstan…

cs.CV2021★ 3 cited

Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning

Jingyu Gong, Jiachen Xu, Xin Tan +4

Hidden features in neural network usually fail to learn informative representation for 3D segmentation as supervisions are only given on output prediction, while this can be solved…

cs.CV2021

Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds

Jingyu Gong, Jiachen Xu, Xin Tan +4

Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in fe…

cs.CV2020★ 6 cited

Analysis on DeepLabV3+ Performance for Automatic Steel Defects Detection

Zheng Nie, Jiachen Xu, Shengchang Zhang

Our works experimented DeepLabV3+ with different backbones on a large volume of steel images aiming to automatically detect different types of steel defects. Our methods applied ra…

cs.CV2020★ 1 cited

SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor

Jiachen Xu, Jingyu Gong, Jie Zhou +3

Besides local features, global information plays an essential role in semantic segmentation, while recent works usually fail to explicitly extract the meaningful global information…