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DiffPop: Plausibility-Guided Object Placement Diffusion for Image Composition

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Jiacheng Liu * , Hang Zhou * , Shida Wei, Rui Ma #

DiffPop: Plausibility-Guided Object Placement Diffusion for Image Composition

SemanticHuman-HD: High-Resolution Semantic Disentangled 3D Human Generation

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Peng Zheng, Tao Liu, Zili Yi, Rui Ma #

SemanticHuman-HD: High-Resolution Semantic Disentangled 3D Human Generation

3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation

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Songchun Zhang, Yibo Zhang, Quan Zheng, Wei Hua, Rui Ma, Hujun Bao, Weiwei Xu, Changqing Zou

3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation

B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

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Hao Wang, Qiang Song, Ruofeng Yin # , Rui Ma #

B-Spine: Learning B-Spline Curve Representation for Robust and Interpretable Spinal Curvature Estimation

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression

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Dong Chen, Ning Liu, Yichen Zhu, Zhengping Che, Rui Ma # , Fachao Zhang, Xiaofeng Mou, Yi Chang, Jian Tang #

EPSD: Early Pruning with Self-Distillation for Efficient Model Compression

P2M2-Net: Part-Aware Prompt-Guided Multimodal Point Cloud Completion

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Linlian Jiang, Pan Chen, Ye Wang, Tieru Wu, Rui Ma #

P2M2-Net: Part-Aware Prompt-Guided Multimodal Point Cloud Completion

MXM-CLR: A Unified Framework for Contrastive Learning of Multifold Cross-Modal Representations

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Ye Wang, Bowei Jiang, Changqing Zou, Rui Ma #

MXM-CLR: A Unified Framework for Contrastive Learning of Multifold Cross-Modal Representations

FD-CAM: Improving Faithfulness and Discriminability of Visual Explanation for CNNs

We propose FD-CAM, a novel CAM (Class activation map) weighting scheme, to improve both the faithfulness and discriminability of the CAM-based CNN visual explanation.

Hui Li, Zihao Li, Rui Ma # , Tieru Wu #

FD-CAM: Improving Faithfulness and Discriminability of Visual Explanation for CNNs

Spatial-Temporal Residual Aggregation for High Resolution Video Inpainting

We propose STRA-Net, a novel spatial-temporal residual aggregation framework for high resolution video inpainting. Our method can produce temporal-coherent inpainting results for high resolution videos efficiently.

Vishnu Sanjay Ramiya Srinivasan * , Rui Ma * , Qiang Tang # , Zili Yi, Zhan Xu

Spatial-Temporal Residual Aggregation for High Resolution Video Inpainting

RaidaR: A Rich Annotated Image Dataset of Rainy Street Scenes

We introduce RaidaR, a rich annotated image dataset of rainy street scenes, to support autonomous driving research. The new dataset contains the largest number of rainy images (58,542) to date, 5,000 of which provide semantic segmentations and 3,658 provide object instance segmentations.

Jiongchao Jin * , Arezou Fatemi * , Wallace Lira, Fenggen Yu, Biao Leng, Rui Ma # , Ali Mahdavi-Amiri, Hao Zhang

RaidaR: A Rich Annotated Image Dataset of Rainy Street Scenes