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AeroDuo: Aerial Duo for UAV-based Vision and Language Navigation
Ruipu Wu, Yige Zhang, Jinyu Chen +5
Aerial Vision-and-Language Navigation (VLN) is an emerging task that enables Unmanned Aerial Vehicles (UAVs) to navigate outdoor environments using natural language instructions an…
Revisiting Audio-Visual Segmentation with Vision-Centric Transformer
Shaofei Huang, Rui Ling, Tianrui Hui +6
Audio-Visual Segmentation (AVS) aims to segment sound-producing objects in video frames based on the associated audio signal. Prevailing AVS methods typically adopt an audio-centri…
Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation
Huan Ren, Wenfei Yang, Xiang Liu +2
Category-level object pose estimation aims to determine the pose and size of novel objects in specific categories. Existing correspondence-based approaches typically adopt point-ba…
Structure-Aware Correspondence Learning for Relative Pose Estimation
Yihan Chen, Wenfei Yang, Huan Ren +3
Relative pose estimation provides a promising way for achieving object-agnostic pose estimation. Despite the success of existing 3D correspondence-based methods, the reliance on ex…
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection
Songhao Han, Wei Huang, Hairong Shi +7
The advancement of Large Vision Language Models (LVLMs) has significantly improved multimodal understanding, yet challenges remain in video reasoning tasks due to the scarcity of h…
TopV-Nav: Unlocking the Top-View Spatial Reasoning Potential of MLLM for Zero-shot Object Navigation
Linqing Zhong, Chen Gao, Zihan Ding +5
The Zero-Shot Object Navigation (ZSON) task requires embodied agents to find a previously unseen object by navigating in unfamiliar environments. Such a goal-oriented exploration h…
Feature Augmentation for Self-supervised Contrastive Learning: A Closer Look
Yong Zhang, Rui Zhu, Shifeng Zhang +3
Self-supervised contrastive learning heavily relies on the view variance brought by data augmentation, so that it can learn a view-invariant pre-trained representation. Beyond incr…
Pamba: Enhancing Global Interaction in Point Clouds via State Space Model
Zhuoyuan Li, Yubo Ai, Jiahao Lu +7
Transformers have demonstrated impressive results for 3D point cloud semantic segmentation. However, the quadratic complexity of transformer makes computation costs high, limiting…
V2X-PC: Vehicle-to-everything Collaborative Perception via Point Cluster
Si Liu, Zihan Ding, Jiahui Fu +4
The objective of the collaborative vehicle-to-everything perception task is to enhance the individual vehicle's perception capability through message communication among neighborin…