SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
PulseAugur coverage of SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks — every cluster mentioning SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks across labs, papers, and developer communities, ranked by signal.
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AI advances sign language translation and video generation
Researchers are exploring advanced AI techniques for sign language translation and generation. One study investigates the impact of different T5 model scales and motion features on translating Indian Sign Language to te…
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Neural operators learn Kohn-Sham map for faster DFT calculations
Researchers have developed a novel approach to density functional theory (DFT) by using neural operators to learn the Kohn-Sham map, which bypasses the computationally intensive orbital diagonalization step. This method…
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Quadcopters achieve IMU-free state estimation using stereo vision
Researchers have developed a novel vision-only state estimation system for quadcopters that does not rely on Inertial Measurement Units (IMUs) or external positioning systems like GPS. The system utilizes a stereo camer…
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New AI models encode anatomical priors to improve medical predictions
Researchers have developed Anatomy-Informed Neural Networks (AINN) to address limitations in deep learning models for anatomical predictions, particularly when training data is scarce. AINN incorporates soft anatomic pr…
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New CVSD-Reg method uses vision models for robust LiDAR registration
Researchers have developed CVSD-Reg, a novel framework for robust global LiDAR registration that leverages visual semantic priors from a vision foundation model. This method distills knowledge from a DINOv2 teacher mode…
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AdvDex framework learns dexterous manipulation from human demonstrations
Researchers have developed AdvDex, a new framework for teaching robots dexterous manipulation skills using human demonstrations. This system utilizes a large-scale dataset called OmniShare, which includes kinematic and …
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New benchmark H2R-Bench reveals limitations in human-to-robot video generation
Researchers have introduced H2R-Bench, a new benchmark designed to evaluate video generation models' ability to translate human manipulation videos into robot-centric demonstrations. The benchmark addresses the challeng…
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New differential pose estimation method enhances robotic motion accuracy
Researchers have developed a novel differential pose estimation method designed to improve accuracy and robustness in 6-DOF motion estimation for robotics and autonomous systems. This new approach directly calculates pl…
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New Polyatomic Complexes representation for atomistic systems unveiled
Researchers have developed a new learning representation for atomistic systems called Polyatomic Complexes, designed to be invariant to physical symmetries and unique. This representation, detailed in a paper submitted …
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New neural network framework learns complex Lie-Poisson system dynamics
Researchers have developed Latent Lie-Poisson Neural Networks (LLPNNs), a novel framework designed to learn and predict the dynamics of Lie-Poisson systems directly from observable data. These systems are crucial for mo…
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New pipeline generates infinite 3D worlds from single panoramas
Researchers have developed Genie Sim PanoWorld, a novel pipeline for generating infinite indoor 3D worlds from a single panoramic image. This system bypasses the need for per-scene optimization or multi-view capture, ad…
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SM4RT Transformer learns structured motion geometry for 4D reconstruction
Researchers have developed SM4RT, a novel Transformer-based model designed for 4D reconstruction and structured motion perception from monocular RGB video. Unlike previous methods that treat motion as independent point-…
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TriGlue: Biology-Inspired Generative Model for Molecular Glue Design
Researchers have introduced TriGlue, a novel generative model inspired by biological mechanisms for designing molecular glues. This model addresses the complex challenge of designing molecular glues, which requires simu…
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New deep learning framework OrbitAll unifies molecular system representation
Researchers have developed OrbitAll, a novel deep learning framework designed to represent all molecular systems using quantum mechanical principles. This framework integrates spin-polarized orbital features with SE(3)-…
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New InertialAR model advances 3D molecule generation with Transformer++
Researchers have developed InertialAR, a novel autoregressive model for generating 3D molecules. This model addresses key challenges in molecule tokenization by creating an SE(3)- and permutation-invariant sequence of t…
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DyneTrion emulator models protein dynamics across timescales
Researchers have developed DyneTrion, a novel generative emulator designed to model protein dynamics across various timescales. This system utilizes a tri-attention architecture that combines SE(3)-robust geometric upda…
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New SeeSE3 method reveals 3D space understanding in vision models
Researchers have developed a new method called SeeSE3 to investigate whether vision foundation models inherently understand 3D Euclidean space. Unlike prior approaches that focus on predicting 3D properties like depth, …
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GenVid2Robot framework translates generated video motion into executable robot trajectories
Researchers have developed GenVid2Robot, a framework that translates generated video motion into executable robot manipulation trajectories. This system addresses the limitations of using generated videos directly for r…
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RayRoPE introduces projective positional encoding for multi-view 3D attention
Researchers have developed RayRoPE, a novel positional encoding method designed for multi-view transformers in 3D computer graphics. This new approach uniquely encodes image patches, enables SE(3)-invariant attention, a…
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New Geometric Observability Index Enhances SE(3) Pose Estimation
Researchers have introduced the Geometric Observability Index (GOI), a novel metric for assessing the sensitivity of pose estimation in SE(3) environments. This index quantifies the influence of individual measurements …