44 skills found · Page 1 of 2
shamangary / FSA Net[CVPR19] FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image
theislab / PagaMapping out the coarse-grained connectivity structures of complex manifolds.
muzishen / IMAGGarment[TVCG 2026] 🎨 IMAGGarment🎨 : Fine-Grained Garment Generation with Controllable Structure, Color, and Logo. It supports precise and customizable garment synthesis guided by multi-conditions (e.g., sketch, color, logo), achieving high realism and controllability for digital fashion design.
Genentech / EquifoldOfficial code repository for EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation
ohtlab / Headpose Fsanet PytorchPytorch implementation of FSA-Net: Learning Fine-Grained Structure Aggregation for Head Pose Estimation from a Single Image
facebookresearch / VCMeshConvLearning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher precision than traditional methods, they remain unable to capture fine-grained deformations. Furthermore, these methods can only be applied to a template-specific surface mesh, and is not applicable to more general meshes, like tetrahedrons and non-manifold meshes. While more general graph convolution methods can be employed, they lack performance in reconstruction precision and require higher memory usage. In this paper, we propose a non-template-specific fully convolutional mesh autoencoder for arbitrary registered mesh data. It is enabled by our novel convolution and (un)pooling operators learned with globally shared weights and locally varying coefficients which can efficiently capture the spatially varying contents presented by irregular mesh connections. Our model outperforms state-of-the-art methods on reconstruction accuracy. In addition, the latent codes of our network are fully localized thanks to the fully convolutional structure, and thus have much higher interpolation capability than many traditional 3D mesh generation models.
wanxueyao / MMGraphRAGMMGraphRAG is a multi-modal knowledge graph-based framework designed to enhance complex reasoning tasks, such as multi-modal document question-answering. It integrates text and image data into a fine-grained, structured knowledge graph, utilizing scene graphs for image data and a spectral clustering-based fusion module.
YPLianGroup / AMCA3DAMCA3D (3D Cellular Automata method for Additive Manufacturing) is a parallel C++ program designed for modeling mesoscale grain structure evolution during the additive manufacturing process.
HVision-NKU / ASID CaptionASID-Caption: Attribute-Structured and Quality-Verified Audiovisual Instruction Dataset and Training Pipeline for Fine-Grained Video Understanding.
huhlim / Cg2allConvert coarse-grained protein structure to all-atom model
MingtaoGuo / CNN For Chinese Calligraphy Styles ClassificationA convolution neural network with SE block and haar wavelet block for Chinese calligraphy styles classification by TensorFlow.(Paper: A novel CNN structure for fine-grained classification of Chinesecalligraphy styles)
IGLICT / RisaNETCode for "RISA-Net: Rotation-Invariant and Structure-Aware Network for Fine-grained 3D Shape Retrieval"
Angusliuuu / Awesome Controllable Generative Models PapersA curated list of recent papers (2023–2025) on controllable generative models, covering diffusion-based architectures with fine-grained control, attention interpretation, spectral manipulation, and structure-preserving image editing. Ideal for researchers and developers exploring controllable synthesis.
MANDO-Project / Ge ScMANDO is a new heterogeneous graph representation to learn the heterogeneous contract graphs' structures to accurately detect vulnerabilities in smart contract source code at both coarse-grained contract-level and fine-grained line-level.
mit-carbon / Flat CombiningTraditional data-structure designs, whether lock-based or lock-free, provide parallelism via fine grained synchronization among threads. Flat Combining is a new, efficient synchronization paradigm based on coarse locking.
nimesh00 / CellularAutomataMicro-structure Grain Growth Simulation
scy-v / ReSemActReSemAct: Advancing Fine-Grained Robotic Manipulation via Semantic Structuring and Affordance Refinement
pkargupta / Tree Of DebateTree-of-Debate converts scientific papers into LLM personas that debate their respective novelties. To emphasize structured, critical reasoning rather than focusing solely on outcomes, Tree-of-Debate dynamically constructs a debate tree, enabling fine-grained analysis of independent novelty arguments within scholarly articles.
EyalMichaeli / SaSPA AugAdvancing Fine-Grained Classification by Structure and Subject Preserving Augmentation with Diffusion Models
havelhakimi / LLM FusionClassifierFine-grained Emotion Classification (FEC) using structured feature fusion from LLaMA-2-7B-Chat, BERT-large, and RoBERTa-large.
