Computer Vision – ECCV 2024

CogView3: Finer and Faster Text-to-Image Generation via Relay Diffusion.- SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers.- Learn to Memorize and to Forget: A Continual Learning Perspective of Dynamic SLAM.- Forecasting Future Videos from Novel Views via Disentangled 3D Scene Representation.- GMM-IKRS: Gaussian Mixture Models for Interpretable Keypoint Refinement and Scoring.- Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest Monitoring.- ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion.- CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning.- Curved Diffusion: A Generative Model With Optical Geometry Control.- Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians.- MeshSegmenter: Zero-Shot Mesh Segmentation via Texture Synthesis.- OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation.- Skeleton Recall Loss for Connectivity Conserving and Resource Efficient Segmentation of Thin Tubular Structures.- Conceptual Codebook Learning for Vision-Language Models.- LingoQA: Video Question Answering for Autonomous Driving.- AnimateMe: 4D Facial Expressions via Diffusion Models.- HaloQuest: A Visual Hallucination Dataset for Advancing Multimodal Reasoning.- LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesis.- PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF Priors.- Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention.- iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning.- Context Diffusion: In-Context Aware Image Generation.- Pose Guided Fine-Grained Sign Language Video Generation.- RAP: Retrieval-Augmented Planner for Adaptive Procedure Planning in Instructional Videos.- Certifiably Robust Image Watermark.- Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery.- Online Zero-Shot Classification with CLIP.