The proceedings contain 16 papers. The special focus in this conference is on Segment Anything in Medical Images on Laptop. The topics include: Filters, Thresholds, and Geodesic Distances for Scribble-Based ...
ISBN:
(纸本)9783031818530
The proceedings contain 16 papers. The special focus in this conference is on Segment Anything in Medical Images on Laptop. The topics include: Filters, Thresholds, and Geodesic Distances for Scribble-Based Interactive Segmentation of Medical Images;Rep-MedSAM: Towards Real-Time and Universal Medical Image Segmentation;Swin-LiteMedSAM: A Lightweight Box-Based Segment Anything Model for Large-Scale Medical Image Datasets;a Light-Weight Universal Medical Segmentation Network for Laptops Based on Knowledge Distillation;taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images;ExpertsMedSAM: Faster Medical Image Segment Anything with Mixture-of-Experts;efficient Quantization-Aware Training on Segment Anything Model in Medical Images and Its Deployment;Lite Class-Prompt Tiny-VIT for Multi-modality Medical Image Segmentation;Segment Anything in Medical Images with nnUNet;SwiftMedSAM: An Ultra-lightweight Prompt-Based Universal Medical Image Segmentation Model for Highly Constrained Environments;RepViT-MedSAM: Efficient Segment Anything in the Medical Images;U-MedSAM: Uncertainty-Aware MedSAM for Medical Image Segmentation;Modality-Specific Strategies for Medical Image Segmentation Using Lightweight SAM Architectures;gray’s Anatomy for Segment Anything Model: Optimizing Grayscale Medical Images for Fast and Lightweight Segmentation.
The proceedings contain 2 papers. The topics discussed include: attention mechanism exploits temporal contexts: real-time 3D human pose reconstruction;and cascaded deep monocular 3D human pose estimation with evolutio...
ISBN:
(纸本)9781728171685
The proceedings contain 2 papers. The topics discussed include: attention mechanism exploits temporal contexts: real-time 3D human pose reconstruction;and cascaded deep monocular 3D human pose estimation with evolutionary training data.
The proceedings contain 2715 papers. The topics discussed include: revisiting adversarial training at scale;SPIDeRS: structured polarization for invisible depth and reflectance sensing;MA-LMM: memory-augmented large m...
ISBN:
(纸本)9798350353006
The proceedings contain 2715 papers. The topics discussed include: revisiting adversarial training at scale;SPIDeRS: structured polarization for invisible depth and reflectance sensing;MA-LMM: memory-augmented large multimodal model for long-term video understanding;geometrically-driven aggregation for zero-shot 3D point cloud understanding;TextCraftor: your text encoder can be image quality controller;ViLa-MIL: dual-scale vision-language multiple instance learning for whole slide image classification;HumanNorm: learning normal diffusion model for high-quality and realistic 3D human generation;AnEmpirical study of scaling law for scene text recognition;improving image restoration through removing degradations in textual representations;and steganographic passport: an owner and user verifiable credential for deep model ip protection without retraining.
The proceedings contain 1658 papers. The topics discussed include: single-stage instance shadow detection with bidirectional relation learning;learning Delaunay surface elements for mesh reconstruction;fusing the old ...
ISBN:
(纸本)9781665445092
The proceedings contain 1658 papers. The topics discussed include: single-stage instance shadow detection with bidirectional relation learning;learning Delaunay surface elements for mesh reconstruction;fusing the old with the new: learning relative camera pose with geometry-guided uncertainty;uncertainty guided collaborative training for weakly supervised temporal action detection;privacy-preserving collaborative learning with automatic transformation search;rethinking and improving the robustness of image style transfer;style-aware normalized loss for improving arbitrary style transfer;faster meta update strategy for noise-robust deep learning;a hyperbolic-to-hyperbolic graph convolutional network;training networks in null space of feature covariance for continual learning;and exponential moving average normalization for self-supervised and semi-supervised learning.
The proceedings contain 1294 papers. The topics discussed include: finding task-relevant features for few-shot learning by category traversal;edge-labeling graph neural network for few-shot learning;generating classif...
ISBN:
(纸本)9781728132938
The proceedings contain 1294 papers. The topics discussed include: finding task-relevant features for few-shot learning by category traversal;edge-labeling graph neural network for few-shot learning;generating classification weights with GNN denoising autoencoders for few-shot learning;kervolutional neural networks;why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem;on the structural sensitivity of deep convolutional networks to the directions of fourier basis functions;hardness-aware deep metric learning;auto-deeplab: hierarchical neural architecture search for semantic image segmentation;striking the right balance with uncertainty;and SDRSAC: semidefinite-based randomized approach for robust point cloud registration without correspondences.
The proceedings contain 802 papers. The topics discussed include: X-VARS: introducing explainability in football refereeing with multi-modal large language models;a hybrid ANN-SNN architecture for low-power and low-la...
ISBN:
(纸本)9798350365474
The proceedings contain 802 papers. The topics discussed include: X-VARS: introducing explainability in football refereeing with multi-modal large language models;a hybrid ANN-SNN architecture for low-power and low-latency visual perception;pseudo-label based unsupervised fine-tuning of a monocular 3D pose estimation model for sports motions;towards efficient audio-visual learners via empowering pre-trained vision transformers with cross-modal adaptation;a dual-mode approach for vision-based navigation in a lunar landing scenario;class similarity transition: decoupling class similarities and imbalance from generalized few-shot segmentation;ReweightOOD: loss reweighting for distance-based OOD detection;Hinge-Wasserstein: estimating multimodal aleatoric uncertainty in regression tasks;and ConPro: learning severity representation for medical images using contrastive learning and preference optimization.
The proceedings contain 355 papers. The topics discussed include: MultiNet++: multi-stream feature aggregation and geometric loss strategy for multi-task learning;privacy-preserving action recognition using coded aper...
ISBN:
(纸本)9781728125060
The proceedings contain 355 papers. The topics discussed include: MultiNet++: multi-stream feature aggregation and geometric loss strategy for multi-task learning;privacy-preserving action recognition using coded aperture videos;evading face recognition via partial tampering of faces;privacy-preserving annotation of face images through attribute-preserving face synthesis;towards deep neural network training on encrypted data;fooling automated surveillance cameras: adversarial patches to attack person detection;anonymousnet: natural face de-identification with measurable privacy;regularizer to mitigate gradient masking effect during single-step adversarial training;privacy preserving group membership verification and identification;defending against adversarial attacks using random forest;intersection to overpass: instance segmentation on filamentous structures with an orientation-aware neural network and terminus pairing algorithm;and surface parameterization and registration for statistical multiscale atlasing of organ development.
The proceedings contain 2356 papers. The topics discussed include: exploring discontinuity for video frame interpolation;two-view geometry scoring without correspondences;language-guided audio-visual source separation...
ISBN:
(纸本)9798350301298
The proceedings contain 2356 papers. The topics discussed include: exploring discontinuity for video frame interpolation;two-view geometry scoring without correspondences;language-guided audio-visual source separation via trimodal consistency;handwritten text generation from visual archetypes;Bayesian posterior approximation with stochastic ensembles;ERM-KTP: knowledge-level machine unlearning via knowledge transfer;PlenVDB: memory efficient VDB-based radiance fields for fast training and rendering;learning and aggregating lane graphs for urban automated driving;teaching matters: investigating the role of supervision in vision transformers;NeuralField-LDM: scene generation with hierarchical latent diffusion models;cut and learn for unsupervised object detection and instance segmentation;probabilistic debiasing of scene graphs;and unifying layout generation with a decoupled diffusion model.
The proceedings contain 523 papers. The topics discussed include: latent fingerprint image enhancement based on progressive generative adversarial network;zero-shot learning in the presence of hierarchically coarsened...
ISBN:
(纸本)9781728193601
The proceedings contain 523 papers. The topics discussed include: latent fingerprint image enhancement based on progressive generative adversarial network;zero-shot learning in the presence of hierarchically coarsened labels;multivariate confidence calibration for object detection;context-guided super-class inference for zero-shot detection;learning sparse ternary neural networks with entropy-constrained trained ternarization (EC2T);now that i can see, i can improve: enabling data-driven finetuning of CNNs on the edge;enhancing facial data diversity with style-based face aging;a simplified framework for zero-shot cross-modal sketch data retrieval;unsupervised single image super-resolution network (USISResNet) for real-world data using generative adversarial network;cross-regional oil palm tree detection;and leaf spot attention network for apple leaf disease identification.
The proceedings contain 698 papers. The topics discussed include: learning unbiased classifiers from biased data with meta-learning;robustness against gradient based attacks through cost effective network fine-tuning;...
ISBN:
(纸本)9798350302493
The proceedings contain 698 papers. The topics discussed include: learning unbiased classifiers from biased data with meta-learning;robustness against gradient based attacks through cost effective network fine-tuning;gradient attention balance network: mitigating face recognition racial bias via gradient attention;estimating and maximizing mutual information for knowledge distillation;synthetic sample selection for generalized zero-shot learning;training strategies for vision transformers for object detection;does image anonymization impact computervision training?;ultra-sonic sensor based object detection for autonomous vehicles;improvements to image reconstruction-based performance prediction for semantic segmentation in highly automated driving;zero-shot classification at different levels of granularity;difficulty estimation with action scores for computervision tasks;detail-preserving self-supervised monocular depth with self-supervised structural sharpening;isolated sign language recognition based on tree structure skeleton images;deep prototypical-parts ease morphological kidney stone identification and are competitively robust to photometric perturbations;wildlife image generation from scene graphs;towards characterizing the semantic robustness of face recognition;high-level context representation for emotion recognition in images;and mitigating catastrophic interference using unsupervised multi-part attention for RGB-IR face recognition.
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