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New 3D silicon chip breakthrough could extend Moore’s Law for years
New 3D silicon chip breakthrough could extend Moore’s Law for years - Date: - May 30, 2026 - Source: - University of Illinois Grainger College of Engineering - Summary: - As traditional chip miniaturization slows, researchers have found a way to pack more computing power into the same space by stacking silicon circuits in multiple layers. The new process uses ultra-thin silicon membranes and low-temperature manufacturing techniques to overcome a major obstacle that has long blocked the...
New 3D microscope technology captures high-resolution tissue images at a fraction of the cost
New 3D microscope technology captures high-resolution tissue images at a fraction of the cost Sadie Harley Scientific Editor Robert Egan Associate Editor A team led by Raju Tomer, professor of biological sciences at Columbia University, has created a new design for microscopes and microscope lenses that could push 3D tissue imaging beyond state-of-the-art systems while drastically cutting costs and complexity. Details of the design were published in the journal Nature Biotechnology. Modern...
From sketch plans to 3D scans: How could new tech change the way Singapore police solved a murder case?
From sketch plans to 3D scans: How could new tech change the way Singapore police solved a murder case? Ten years ago, police used sketches and photographs to reconstruct the crime scene in the Tanah Merah Ferry Terminal murder. But how could 3D scanners and drones have changed the way police solved the case?
HOLA: Holistic Multi-Modal Alignment for Open-Set 3D Recognition
Announce Type: new Abstract: Open-set 3D recognition requires models that generalize to rare or unseen categories. Recent approaches address this by distilling language-vision knowledge into 3D encoders, typically relying on heavy 2D ViTs and aligning each point cloud with a single image or caption, thus anchoring representations to partial views. We propose aligning each point cloud with multiple images and textual descriptions to capture a more holistic understanding of 3D objects.
SymTRELLIS: Symmetry-Enforced Voxel Latents for 3D Generation
Announce Type: new Abstract: Single-view 3D generative models have achieved impressive visual quality, yet they are not designed to satisfy structural or functional requirements, and in practice, often fall short. Symmetry is one such requirement: violations, even subtle ones, on symmetry can render a model physically unusable. We present SymTRELLIS, a method that enforces arbitrary finite point group symmetries (rotational, reflectional, and polyhedral) during the flow-based 3D generation...
T-FunS3D: Task-Driven Hierarchical Open-Vocabulary 3D Functionality Segmentation
Announce Type: new Abstract: Open-vocabulary 3D functionality segmentation enables robots to localize functional object components in 3D scenes. It is a challenging task that requires spatial understanding and task interpretation. Current open-vocabulary 3D segmentation methods primarily focus on object-level recognition, while scene-wide part segmentation methods attempt to segment the entire scene exhaustively, making them highly resource-intensive and time consuming.
EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs
Announce Type: new Abstract: Deep learning surrogates for 3D Partial Differential Equations (PDEs) often fail to generalize across geometric transformations because they depend heavily on specific coordinate systems. While equivariant networks offer a solution, they typically rely on local operations in the spatial domain, making the global receptive field, which is essential for PDE dynamics, computationally expensive. Conversely, Fourier Neural Operators (FNOs) efficiently capture global...
PillarDETR: YOLO-Backbone and RT-DETR Head for Real-Time 3D Object Detection
Announce Type: new Abstract: Real-time 3D object detection is a critical component for the safe operation of autonomous driving systems and robotics. While LiDAR point clouds provide accurate spatial information, processing them efficiently remains a significant challenge. Traditional methods rely on complex 3D convolutions or anchor-based paradigms that struggle to balance detection accuracy with inference speed.
Spatially Uniform and Defect-Tolerant Plasmonic Responses in 3D printed Gold Nanoparticle Assemblies
new Abstract: Three-dimensional (3D) assemblies of gold nanoparticles (AuNPs) offer a rich platform for plasmonic coupling and near-field engineering, yet their optical behavior is often complex due to structural disorder and fabrication-induced variability. Here, we present a systematic optical investigation of large-scale 3D AuNP assemblies fabricated via meniscus-guided assembly, focusing on the reproducibility and spatial uniformity. Spatially-resolved dark-field scattering measurements...
Path-Traced Inverse Rendering with Global Illumination in 3D Gaussian Fields
Announce Type: new Abstract: Ray tracing enables 3D Gaussian fields to serve as a representation for physically based light transport. Faithful inverse rendering requires forward rendering and backward optimization to be defined within a consistent light-transport pipeline. Existing inverse rendering methods estimate G-buffers via splatting and optimize materials in screen space, tying the recovered properties to a rasterization-based pipeline.