14 accepted papers
We present Online3R, a new sequential reconstruction framework that is capable of adapting to new scenes through online learning, effectively resolving inconsistency issues. Specifically, we introduce a set of learnable lightweight visual prompts into a pretrained, frozen geometry foundation model t
Understanding objects in dynamic 4D environments via natural language is crucial yet underexplored. While existing methods focus on static 3D referring segmentation or open-vocabulary 4D querying, they struggle to ground complex spatio-temporal referring expressions in explicit 4D reconstructions. W
Mixture-of-Experts (MoE) models achieve a favorable trade-off between performance and inference efficiency by activating only a subset of experts. However, the memory overhead of storing all experts remains a major limitation, especially in large-scale MoE models such as DeepSeek-R1 (671B). In this…
Machine unlearning (MU) aims to efficiently remove sensitive or harmful memory from a pre-trained model. The key challenge is to balance the potential tradeoff between unlearning efficacy and utility preservation, which involves forgetting undesirable information as defined while maintaining the mod…
Human behaviors are the major causes of scene dynamics and inherently contain rich cues regarding the dynamics. This paper formalizes a new task of proactive scene decomposition and reconstruction, an online approach that leverages human-object interactions to iteratively disassemble and reconstruct…
"Simultaneous localization and mapping (SLAM) with implicit neural representations has received extensive attention due to the expressive representation power and the innovative paradigm of continual learning. However, deploying such a system within a dynamic environment has not been well-studied. S…
We introduce the Panoptic 3D Reconstruction task a unified and holistic scene understanding task for a monocular video. And we present PanoRecon - a novel framework to address this new task which realizes an online geometry reconstruction alone with dense semantic and instance labeling. Specifically…
With the increasing customization of spectrometers, spectral unmixing has become a widely used technique in fields such as remote sensing, textiles, and environmental protection. However, endmember variability is a common issue for unmixing, where changes in lighting, atmospheric, temporal condition…
Textile composition identification (TCI) is an essential basic link in the textile industry. Methods based on computer vision or near-infrared (NIR) signal processing have shown potential for the nondestructive TCI task. However, these methods ignore that the integration of NIR signals and visual in…
Bipartite graphs have been widely used in many applications such as recommender systems, search engines and so on. Recent works consider bipartite graphs as homogeneous graphs and apply graph convolution networks for link prediction or node classification. However, in bipartite graphs, there are two…
Knowledge graphs can help improve the performance of recommender systems by mitigating sparsity and cold-start problems. However, existing approaches usually suffer from problems of domain distribution matching and cycle consistency for co-representation learning, as the representations of items fro…
Near Infrared (NIR) Spectral signal has been successfully applied to fabric component analysis (FCA), which is used to identify the category of the textile (defined as a classification task) and its corresponding content for that category (defined as a regression problem). Unlike conventional classi…
Video content is multifaceted, consisting of objects, scenes, interactions or actions. The existing datasets mostly label only one of the facets for model training, resulting in the video representation that biases to only one facet depending on the training dataset. There is no study yet on how to…
Simultaneous motion control of multiple joints has many potential applications such as Tai Chi, Yoga etc. The capability of vibrotactile cues to assist this kind of motor task has not been well explored. In this paper, we studied the effect of vibrotactile cues for guiding procedural motion of two j…