Computer Vision ECCV 2024: 18th European Conference, Milan, Italy, September 29October 4, 2024, Proceedings, Part XXX 2024 ed. [Pehme köide]

SemanticHuman-HD: High Resolution Semantic disentangled 3D Human
Generation.- CoherentGS: Sparse Novel View Synthesis with Coherent 3D
Gaussians.- Monocular Occupancy Prediction for Scalable Indoor Scenes.-
Visual Grounding for Object-Level Generalization in Reinforcement Learning.-
3DEgo: 3D Editing on the Go!.- Efficient Depth-Guided Urban View Synthesis.-
Probabilistic Weather Forecasting with Deterministic Guidance-based Diffusion
Model.- Domain-adaptive Video Deblurring via Test-time Blurring.-
Representing Topological Self-Similarity Using Fractal Feature Maps for
Accurate Segmentation of Tubular Structures.- NeuroNCAP: Photorealistic
Closed-loop Safety Testing for Autonomous Driving.- OLAF: A Plug-and-Play
Framework for Enhanced Multi-object Multi-part Scene Parsing.- Progressive
Pretext Task Learning for Human Trajectory Prediction.- Hyperion A fast,
versatile symbolic Gaussian Belief Propagation framework for Continuous-Time
SLAM.- Isomorphic Pruning for Vision Models.- Attention Prompting on Image
for Large Vision-Language Models.- Learning Cross-hand Policies of High-DOF
Reaching and Grasping.- Reprojection Errors as Prompts for Efficient Scene
Coordinate Regression.- Diffusion-Driven Data Replay: A Novel Approach to
Combat Forgetting in Federated Class Continual Learning.- Long-Tail Temporal
Action Segmentation with Group-wise Temporal Logit Adjustment.- REVISION:
Rendering Tools Enable Spatial Fidelity in Vision-Language Models.-
DreamMotion: Space-Time Self-Similar Score Distillation for Zero-Shot Video
Editing.- VideoClusterNet: Self-Supervised and Adaptive Face Clustering for
Videos.- Unveiling Privacy Risks in Stochastic Neural Networks Training:
Effective Image Reconstruction from Gradients.- Controlling the World by
Sleight of Hand.- Hiding Imperceptible Noise in Curvature-Aware Patches for
3D Point Cloud Attack.- Interleaving One-Class and Weakly-Supervised Models
with Adaptive Thresholding for Unsupervised Video Anomaly Detection.-
Cross-Domain Learning for Video Anomaly Detection with Limited Supervision.