8 papers
UniAfford: Token-Routed Multitask Learning for Generalizable 2D-3D Affordance Perception
Yuhao Liu, Yiming Zhong, Hanqing Wang +9
Affordance perception aims to localize actionable regions supporting embodied interaction, yet 2D and 3D affordance grounding have evolved as separate problems, with different task…
Not All Attention Heads Contribute to Critical Visual Token Selection: Head-Aware Pruning Matters More
Chaofang Ma, Lin Jiang, Carol Jingyi Li +4
Vision-Language Models (VLMs) have exhibited impressive performance across diverse visual scenarios. However, this success comes at the cost of explosive growth in visual tokens, w…
Not All Tasks Quantize Equally: Fisher-Guided Quantization for Visual Geometry Transformer
Yipu Zhang, Jintao Cheng, Weilun Feng +5
Feed-forward 3D reconstruction models, represented by Visual Geometry Grounded Transformer (VGGT), jointly predict multiple visual geometry tasks such as depth estimation, camera p…
Training-Free Interaction-Aligned Visual Token Pruning for Efficient Embodied Manipulation
Jintao Cheng, Weibin Li, Haozhe Wang +7
Efficient visual representation is a central image-processing challenge in embodied manipulation, where policies repeatedly process dense visual-token sequences during closed-loop…
Beyond First-Order: Learning Riemannian Geometries for Invariant Visual Place Recognition
Jintao Cheng, Weibin Li, Zhijian He +3
Visual Place Recognition (VPR) demands representations robust to drastic environmental and viewpoint shifts. Existing aggregation paradigms either depend on extensive supervised tr…
VersaQ-3D: Architecture Support for Visual Geometry Grounded Transformers via Versatile Quantization
Yipu Zhang, Jintao Cheng, Xingyu Liu +8
3D reconstruction and view synthesis are fundamental to AR/VR, robotics, and digital twins. The Visual Geometry Grounded Transformer (VGGT) enables strong feed-forward 3D reconstru…
Scale, Don't Fine-tune: Guiding Multimodal LLMs for Efficient Visual Place Recognition at Test-Time
Jintao Cheng, Weibin Li, Jiehao Luo +5
Visual Place Recognition (VPR) has evolved from handcrafted descriptors to deep learning approaches, yet significant challenges remain. Current approaches, including Vision Foundat…
A Pseudo Global Fusion Paradigm-Based Cross-View Network for LiDAR-Based Place Recognition
Jintao Cheng, Jiehao Luo, Xieyuanli Chen +4
LiDAR-based Place Recognition (LPR) remains a critical task in Embodied Artificial Intelligence (AI) and Autonomous Driving, primarily addressing localization challenges in GPS-den…