CineMatte uses a cross-attention design on a Siamese DINOv3 ViT plus a pretrained upsampler to produce robust mattes for virtual production, backed by a new non-synthetic 4K VP dataset that supports camera motion.
Segformer: Simple and efficient design for semantic segmentation with transform- ers.Advances in neural information processing systems, 34: 12077–12090
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A dual-stream vision transformer with modality-aware gated exchange and bidirectional token exchange fuses RGB, thermal, and event data to improve UAV vehicle detection over dual-modal baselines on a new 10,489-frame dataset.
SparseSplat uses entropy-based probabilistic sampling and a specialized point cloud network to generate compact 3D Gaussian maps that retain high rendering quality with far fewer Gaussians than prior feed-forward methods.
citing papers explorer
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CineMatte: Background Matting for Virtual Production and Beyond
CineMatte uses a cross-attention design on a Siamese DINOv3 ViT plus a pretrained upsampler to produce robust mattes for virtual production, backed by a new non-synthetic 4K VP dataset that supports camera motion.
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Tri-Modal Fusion Transformers for UAV-based Object Detection
A dual-stream vision transformer with modality-aware gated exchange and bidirectional token exchange fuses RGB, thermal, and event data to improve UAV vehicle detection over dual-modal baselines on a new 10,489-frame dataset.
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SparseSplat: Towards Applicable Feed-Forward 3D Gaussian Splatting with Pixel-Unaligned Prediction
SparseSplat uses entropy-based probabilistic sampling and a specialized point cloud network to generate compact 3D Gaussian maps that retain high rendering quality with far fewer Gaussians than prior feed-forward methods.