| 1 |
Splannequin: Freezing Monocular Mannequin-Challenge Footage with Dual-Detection Splatting |
Splannequin:利用双重检测 Splatting 冻结单目人体雕塑挑战视频 |
gaussian splatting splatting scene reconstruction |
✅ |
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| 2 |
4DLangVGGT: 4D Language-Visual Geometry Grounded Transformer |
提出4DLangVGGT,用于高效且可泛化的4D语言-视觉几何联合理解 |
gaussian splatting splatting scene understanding |
✅ |
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| 3 |
RobustSplat++: Decoupling Densification, Dynamics, and Illumination for In-the-Wild 3DGS |
提出RobustSplat++以解决动态与光照影响下的3D高斯渲染问题 |
3D gaussian splatting 3DGS gaussian splatting |
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| 4 |
Towards Adaptive Fusion of Multimodal Deep Networks for Human Action Recognition |
提出基于门控机制的多模态自适应融合网络,用于提升人类行为识别精度。 |
optical flow multimodal |
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| 5 |
The SAM2-to-SAM3 Gap in the Segment Anything Model Family: Why Prompt-Based Expertise Fails in Concept-Driven Image Segmentation |
分析SAM2到SAM3的断层:探究提示工程在概念驱动图像分割中的失效原因 |
open-vocabulary open vocabulary foundation model |
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| 6 |
Gaussian Entropy Fields: Driving Adaptive Sparsity in 3D Gaussian Optimization |
提出高斯熵场以驱动3D高斯优化中的自适应稀疏性 |
3D gaussian splatting 3DGS gaussian splatting |
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| 7 |
LiteVGGT: Boosting Vanilla VGGT via Geometry-aware Cached Token Merging |
LiteVGGT:通过几何感知缓存Token合并加速VGGT,实现大规模场景高效3D重建。 |
VGGT foundation model |
✅ |
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| 8 |
SAM3-I: Segment Anything with Instructions |
SAM3-I:通过指令感知的级联自适应机制增强SAM3,实现指令驱动的图像分割 |
open-vocabulary open vocabulary instruction following |
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| 9 |
Malicious Image Analysis via Vision-Language Segmentation Fusion: Detection, Element, and Location in One-shot |
提出基于视觉-语言分割融合的恶意图像分析方法,实现一步到位的内容检测、元素识别和定位。 |
open-vocabulary open vocabulary |
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| 10 |
UTrice: Unifying Primitives in Differentiable Ray Tracing and Rasterization via Triangles for Particle-Based 3D Scenes |
UTrice:通过三角形统一可微光线追踪与栅格化,用于基于粒子的3D场景渲染 |
splatting |
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