10 accepted papers
Image geo-localization aims to determine the geographic location of a query image. While Multimodal Large Language Models (MLLMs) show potential for this task due to their rich world knowledge and explainable abilities, they often struggle with confirmation bias, i.e., committing to early, potential
4D Gaussian Splatting (4DGS) enables high-quality, real-time rendering of dynamic scenes and is becoming a popular format for sharing 4D assets. This trend calls for robust copyright watermarking that can be verified from rendered videos without access to the original scene or model parameters. Howe
The rapid evolution of generative AI, including such models as Sora, has intensified the threat of video misinformation. A critical challenge in detecting these AI-generated video misinformation lies in a fundamental disconnect between existing datasets and practical deception tactics. Current datas
3D lane detection aims to identify lane categories and trends in 3D space, which is a vital and challenging task in autonomous driving. Existing methods introduce various priors to guide 3D lane prediction, which generally consist of a series of reference points for context aggregation. However, due
Out-of-distribution (OOD) detection aims to distinguish whether detected objects belong to known categories or not. Existing methods extract OOD samples from In-distribution (ID) data to regularize the model's decision boundaries. However, the decision boundaries are not adequately regularized becau…
Few-shot Open-set Object Detection (FOOD) poses a challenge in many open-world scenarios. It aims to train an open-set detector to detect known objects while rejecting unknowns with scarce training samples. Existing FOOD methods are subject to limited visual information, and often exhibit an ambiguo
Existing incremental few-shot semantic segmentation (IFSS) methods often learn novel classes by fine-tuning parameters from previous stages. This inevitably reduces the distinguishability of old class features, leading to catastrophic forgetting and overfitting to limited new samples. In this paper,…
Scene Coordinate Regression (SCR) estimates 3D scene coordinates from 2D images, and has become an important approach in visual relocalization. Existing methods exhibit high localization accuracy in small scenes, but still face substantial challenges in large-scale scenes, which usually have signifi
Crowd counting has drawn more and more attention in computer vision. There are two mainstream approaches to deal with crowd counting tasks, regression and detection. Regression-based methods usually overestimate the count in sparse areas, while detection-based methods tend to underestimation in dens…
Vehicle re-identification (re-id) plays an important role in intelligent surveillance. Since difference vehicle models may have similar appearances, together with the problem of image scale variations, the vehicle re-id remains long-term challenging. We present a novel multi-scale vehicle re-id fram…