Description
Book SynopsisSemantic Residual Prompts for Continual Learning.- TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds.- ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling.- Mixture of Efficient Diffusion Experts Through Automatic Interval and Sub-Network Selection.- Occupancy as Set of Points.- UAV First-Person Viewers Are Radiance Field Learners.- Rethinking Few-shot Class-incremental Learning: Learning from Yourself.- ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection.- A Fair Ranking and New Model for Panoptic Scene Graph Generation.- Pick-a-back: Selective Device-to-Device Knowledge Transfer in Federated Continual Learning.- Compensation Sampling for Improved Convergence in Diffusion Models.- Situated Instruction Following.- Holodepth: Programmable Depth-Varying Projection via Computer-Generated Holography.- SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model.- GalLop: Learning global and local prompts for vision-language models.- Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active Sensor.- Lossy Image Compression with Foundation Diffusion Models.- CLIP-DINOiser: Teaching CLIP a few DINO tricks for open-vocabulary semantic segmentation.- FMBoost: Boosting Latent Diffusion with Flow Matching.- COMPOSE: Comprehensive Portrait Shadow Editing.- LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration.- Diffusion Models as Data Mining Tools.- Graph Neural Network Causal Explanation via Neural Causal Models.- Unsupervised, Online and On-The-Fly Anomaly Detection For Non-Stationary Image Distributions.- Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering.- GAReT: Cross-view Video Geolocalization with Adapters and Auto-Regressive Transformers.- SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather.
