VINS-120K supplies the first large-scale set of instruction-image-edited-image triplets at ultra-high resolution together with an adaptation strategy that improves detail synthesis.
Attention is all you need.Advances in neural information processing systems, 30, 2017
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WD-FQDet decouples modality-shared and modality-specific features in infrared-visible images via wavelet-based frequency decomposition and frequency-aware query selection to achieve state-of-the-art detection performance.
AssemblyBench dataset and AssemblyDyno transformer model enable physics-aware prediction of assembly sequences and trajectories for complex industrial objects from multimodal instructions and 3D shapes.
C-MET transfers emotions from speech to facial video by learning cross-modal semantic vectors with pretrained audio and disentangled expression encoders, yielding 14% higher emotion accuracy on MEAD and CREMA-D even for unseen emotions.
MoGaF groups Gaussians by motion in 4D splatting representations to enable stable long-term forecasting of dynamic scenes.
Pointer-CAD unifies B-Rep geometry with command sequences via pointer-based entity selection, allowing LLMs to perform complex CAD edits while cutting topological errors from quantization.
SGSoft introduces a template-guided pipeline that fuses semantic and geometric features to learn dense correspondences across deformable 3D shapes with claimed SOTA generalization and real-time efficiency.
SD-MVSum extends script-driven video summarization to multimodal inputs by modeling script-video and script-transcript relevance with a new weighted cross-modal attention mechanism, plus extended S-VideoXum and MrHiSum datasets.
citing papers explorer
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VINS-120K: Ultra High-Resolution Image Editing with A Large-Scale Dataset
VINS-120K supplies the first large-scale set of instruction-image-edited-image triplets at ultra-high resolution together with an adaptation strategy that improves detail synthesis.
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WD-FQDet: Multispectral Detection Transformer via Wavelet Decomposition and Frequency-aware Query Learning
WD-FQDet decouples modality-shared and modality-specific features in infrared-visible images via wavelet-based frequency decomposition and frequency-aware query selection to achieve state-of-the-art detection performance.
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AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects
AssemblyBench dataset and AssemblyDyno transformer model enable physics-aware prediction of assembly sequences and trajectories for complex industrial objects from multimodal instructions and 3D shapes.
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Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video
C-MET transfers emotions from speech to facial video by learning cross-modal semantic vectors with pretrained audio and disentangled expression encoders, yielding 14% higher emotion accuracy on MEAD and CREMA-D even for unseen emotions.
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Space-Time Forecasting of Dynamic Scenes with Motion-aware Gaussian Grouping
MoGaF groups Gaussians by motion in 4D splatting representations to enable stable long-term forecasting of dynamic scenes.
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Pointer-CAD: Unifying B-Rep and Command Sequences via Pointer-based Edges & Faces Selection
Pointer-CAD unifies B-Rep geometry with command sequences via pointer-based entity selection, allowing LLMs to perform complex CAD edits while cutting topological errors from quantization.
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SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals
SGSoft introduces a template-guided pipeline that fuses semantic and geometric features to learn dense correspondences across deformable 3D shapes with claimed SOTA generalization and real-time efficiency.
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SD-MVSum: Script-Driven Multimodal Video Summarization Method and Datasets
SD-MVSum extends script-driven video summarization to multimodal inputs by modeling script-video and script-transcript relevance with a new weighted cross-modal attention mechanism, plus extended S-VideoXum and MrHiSum datasets.