Chamfer
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Related Articles from SNS
Approximate Algorithms for Chamfer Distance Under Translation
arXiv:2605.25280v2 Announce Type: replace Abstract: Given two sets of points A and B, $|A| = m$, $|B| = n$, the Chamfer distance from $A$ to $B$ is defined as $\operatorname{CD}(A,B) = \sum_{a\in A} \min_{b\in B} d(a,b)$, where $d$ is a distance metric. Chamfer distance is a popular measure of dissimilarity between two sets of points that has seen increasing usage in computer vision and information retrieval as a substitute for the more computationally demanding Earth Mover's distance.
3D Oral Modelling with Improved Vertex Distribution Using Matching-Based Learning
arXiv:2606.07907v1 Announce Type: new Abstract: In our previous work, a deep learning-based framework for 3D intraoral reconstruction was proposed. The model directly predicts explicit 3D point cloud coordinates from ten fixed-angle intraoral images, employing MobileNetV2 and Multi-head Attention for multi-view feature fusion, with a combined L1 Loss and Chamfer Distance as the loss function. Although the model achieved an accuracy of 77.49%, predicted vertices tended to concentrate in...
Cloning a Sennheiser BA2015 battery pack
One of the annoying things about electronics is that so many companies must make their own incompatible battery packs. For many products these are expensive but at some level still reasonable, the battery pack contains the protection circuitry and some guaranteed high quality Li-ion cells. This is not one of those devices.
CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
Announce Type: replace Abstract: Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for design and manufacturing, as existing CAD reconstruction and generation methods are largely restricted to difficult-to-edit formats like meshes or Breps or editable simple sketch-and-extrude pipelines and low-complexity datasets. We introduce CADFit, a hybrid optimization-based CAD reconstruction framework that...
CADFit: Precise Mesh-to-CAD Program Generation with Hybrid Optimization
Announce Type: replace Abstract: Despite recent progress, recovering parametric CAD construction sequences from geometric input, such as meshes or point clouds, is a key challenge for design and manufacturing, as existing CAD reconstruction and generation methods are largely restricted to difficult-to-edit formats like meshes or Breps or editable simple sketch-and-extrude pipelines and low-complexity datasets. We introduce CADFit, a hybrid optimization-based CAD reconstruction framework that...
reMarkable Paper Pure review: Great hardware held back by bad philosophy
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R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search
arXiv:2606.04823v1 Announce Type: new Abstract: Large language models (LLMs) are fluent on open-ended tasks, yet in agentic settings, where a system must plan, use tools, and act over extended horizons, fluency does not ensure reliable delivery. We trace this gap to three coupled structural failures: errors propagate without localization, worst-case perturbations go unevaluated, and accumulated knowledge is never invalidated. We argue these share a root cause: abductive, counterfactual,...
RISE: Single Static Radar-based Indoor Scene Understanding
arXiv:2511.14019v3 Announce Type: replace Abstract: Robust and privacy-preserving indoor scene understanding remains a fundamental open problem. While optical sensors such as RGB and LiDAR offer high spatial fidelity, they suffer from severe occlusions and introduce privacy risks in indoor environments. In contrast, millimeter-wave (mmWave) radar preserves privacy and penetrates obstacles, but its inherently low spatial resolution makes reliable geometric reasoning difficult.
PerBite: A Curated Diagnostic Workflow for Bite-Aware Food Volume Estimation
Announce Type: new Abstract: Can a visually plausible food mesh be trusted to estimate the volume of consumed food? \method investigates this question using selected paired before- and after-consumption states from the MetaFood CVPR 2026 Continuous 3D Reconstruction While Eating Challenge. The submitted workflow follows a curated reconstruction protocol: SAM~3 segments the food and plate regions; Hunyuan3D/SAM~3D generates a dimensionless food mesh; the plate diameter provides the metric...
Highly Deformable Proprioceptive Membrane for Real-Time 3D Shape Reconstruction
Announce Type: replace Abstract: Reconstructing the three-dimensional (3D) geometry of object surfaces is essential for robot perception, yet vision-based approaches degrade under low illumination or occlusion. This limitation motivates the design of a proprioceptive membrane that conforms to the surface of interest and infers 3D geometry by reconstructing its own deformation. Conventional deformation-aware membranes typically rely on resistive, capacitive, or magneto-sensitive mechanisms,...