14 accepted papers
Navigating unseen environments based on natural language instructions remains difficult for egocentric agents in Vision-and-Language Navigation (VLN). Intuitively, humans inherently ground concrete semantic knowledge within spatial layouts during indoor navigation. Although previous studies have i
Text-to-Video (T2V) generation has advanced greatly, yet maintaining consistency remains challenging, especially for tuning-free long video generation. We attribute the consistency problem to cumulative deviations for long video generation at three levels: the random noise lacking correlation resu
Open-vocabulary part segmentation (OVPS) aims to segment objects into fine-grained parts while generalizing to unseen categories. Existing VLM-based methods face two challenges: (1) object over-segmentation, caused by overly broad semantic activations, and (2) part under-segmentation, resulting from
Dexterous robotic hands enable robots to perform complex manipulations that require fine-grained control and adaptability. Achieving such manipulation is challenging because the high degrees of freedom tightly couple hand and arm motions, making learning and control difficult. Successful dexterous m…
Based on an RGB-D image pair, semantic scene completion (SSC) provides a description for 3D scene understanding by predicting 3D semantic occupancy map. Recent methods extract RGB-D multi-modal features and fuse them in spatial domain, which disregards the misalignment caused by the imperfect raw mu
Vision-and-Language Navigation in Continuous Environments (VLN-CE) presents challenges due to environmental variations and domain shifts, making it difficult for agents to generalize beyond seen environments. Most existing methods rely on learning correlations between observations and actions from t
Spike-based imaging, inspired by the human visual system, offers several advantages, including high temporal resolution and low power consumption, but suffers from significant image degradation in low-light conditions due to noise interference. Restoring spike images under such conditions poses a si…
High-quality video generation is crucial for many fields, including the film industry and autonomous driving. However, generating videos with spatiotemporal consistencies remains challenging. Current methods typically utilize attention mechanisms or modify noise to achieve consistent videos, neglect…
Open-vocabulary part segmentation (OVPS) struggles with structurally connected boundaries due to the inherent conflict between continuous image features and discrete classification mechanism. To address this, we propose PBAPS, a novel training-free framework specifically designed for OVPS. PBAPS lev…
Pedestrian trajectory prediction ensures safe navigation in autonomous driving and intelligent robots. Existing methods have shown promising results but still face challenges in handling dynamic environments, social interactions, and high-dimensional data. In this paper, we propose a novel PhysGCN-D
Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to navigate with lowlevel actions following natural language instructions in 3D environments. Most existing approaches utilize observation features from the current step to represent the viewpoint. However, these repr
Vision-and-Language Navigation (VLN) in continuous environments aims to navigate robot agents in unseen environments following natural language instructions. The majority of existing approaches rely on constructing semantic maps or topological maps to record information. However, semantic maps overl…
Semantic scene completion is a difficult task that involves completing the geometry and semantics of a scene from point clouds in a large-scale environment. Many current methods use 3D/2D convolutions or attention mechanisms, but these have limitations in directly constructing geometry and accuratel…
Image rain removal requires the accurate separation between the pixels of the rain streaks and object textures. But the confusing appearances of rains and objects lead to the misunderstanding of pixels, thus remaining the rain streaks or missing the object details in the result. In this paper, we pr…