43 citations · 49 across the 5 of their papers we have counts for
5 papers
SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer
Xuanyao Chen, Zhijian Liu, Haotian Tang +3
High-resolution images enable neural networks to learn richer visual representations. However, this improved performance comes at the cost of growing computational complexity, hind…
ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queries
Junru Gu, Chenxu Hu, Tianyuan Zhang +4
Perception and prediction are two separate modules in the existing autonomous driving systems. They interact with each other via hand-picked features such as agent bounding boxes a…
MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries
Tianyuan Zhang, Xuanyao Chen, Yue Wang +2
Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-based autonomous driving system. It involves modeling 3D dynamic objects in complex scenes…
FUTR3D: A Unified Sensor Fusion Framework for 3D Detection
Xuanyao Chen, Tianyuan Zhang, Yue Wang +2
Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics. Existing multi-modal 3D detection models usually involve customized designs…
What Makes Multi-modal Learning Better than Single (Provably)
Yu Huang, Chenzhuang Du, Zihui Xue +3
The world provides us with data of multiple modalities. Intuitively, models fusing data from different modalities outperform their uni-modal counterparts, since more information is…