Computer Vision – ECCV 2022

Explicit Model Size Control and Relaxation via Smooth Regularization for Mixed-Precision Quantization.- BASQ: Branch-Wise Activation-Clipping Search Quantization for Sub-4-Bit Neural Networks.- You Already Have It: A Generator-Free Low-Precision DNN TrainingFramework Using Stochastic Rounding.- Real Spike: Learning Real-Valued Spikes for Spiking Neural Networks.- FedLTN: Federated Learning for Sparse and Personalized Lottery Ticket Networks.- Theoretical Understanding of the Information Flow on ContinualLearning Performance.- Exploring Lottery Ticket Hypothesis in Spiking Neural Networks.- On the Angular Update and Hyperparameter Tuning of a Scale-Invariant Network.- LANA: Latency Aware Network Acceleration.- RDO-Q: Extremely Fine-Grained Channel-Wise Quantization via Rate-Distortion Optimization.- U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search.- PTQ4ViT: Post-Training Quantization for Vision Transformers with Twin Uniform Quantization.- Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach.- Understanding the Dynamics of DNNs Using Graph Modularity.- Latent Discriminant Deterministic Uncertainty.- Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals.- HIVE: Evaluating the Human Interpretability of Visual Explanations.- BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks.- SESS: Saliency Enhancing with Scaling and Sliding.- No Token Left Behind: Explainability-Aided Image Classification and Generation.- Interpretable Image Classification with Differentiable Prototypes Assignment.- Contributions of Shape, Texture, and Color in Visual Recognition.- STEEX: Steering Counterfactual Explanations with Semantics.- Are Vision Transformers Robust to Patch Perturbations?.- A Dataset Generation Framework for Evaluating Megapixel Image Classifiers & Their Explanations.- Cartoon Explanations of Image Classifiers.- Shap-CAM: Visual Explanations for Convolutional Neural NetworksBased on Shapley Value.- Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain.- Contrast-Phys: Unsupervised Video-Based Remote Physiological Measurement via Spatiotemporal Contrast.- Source-Free Domain Adaptation with Contrastive Domain Alignment and Self-Supervised Exploration for Face Anti-Spoofing.- On Mitigating Hard Clusters for Face Clustering.- OneFace: One Threshold for All.- Label2Label: A Language Modeling Framework for Multi Attribute Learning.- AgeTransGAN for Facial Age Transformation with Rectified Performance Metrics.- Hierarchical Contrastive Inconsistency Learning for Deepfake Video Detection.- Rethinking Robust Representation Learning under Fine-Grained Noisy Faces.- Teaching Where to Look: Attention Similarity Knowledge Distillationfor Low Resolution Face Recognition.- Teaching with Soft Label Smoothing for Mitigating Noisy Labels in Facial Expressions.- Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis.- CoupleFace: Relation Matters for Face Recognition Distillation.- Controllable and Guided Face Synthesis for Unconstrained Face Recognition.- Towards Robust Face Recognition with Comprehensive Search.- Towards Unbiased Label Distribution Learning for Facial Pose Estimation Using Anisotropic Spherical Gaussian.