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Name: Fudan Zhang Vision Group
Type: Organization
Bio: Zhang Vision Group at the School of Data Science of the Fudan University
Location: Shanghai, China
Name: Fudan Zhang Vision Group
Type: Organization
Bio: Zhang Vision Group at the School of Data Science of the Fudan University
Location: Shanghai, China
[ICLR 2024] Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splatting
[CVPR 2021] Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detection
[NeurIPS 2022] DeepInteraction: 3D Object Detection via Modality Interaction
[TPAMI 2022 & CVPR 2020 Oral] Dynamic Graph Message Passing Networks
[ECCV 2022] Learning Ego 3D Representation as Ray Tracing
[CVPR 2023] Official repository of Generative Semantic Segmentation
[AAAI 2024] NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields
[ICCV 2023] PARTNER: Level up the Polar Representation for LiDAR 3D Object Detection
[ECCV 2022] Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling
[ICLR 2024] Enhancing High-Resolution 3D Generation through Pixel-wise Gradient Clipping
[AAAI 2023] PolarFormer: Multi-camera 3D Object Detection with Polar Transformers
Progressive Coordinate Transforms for Monocular 3D Object Detection, NeurIPS 2021
Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering
Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
[ICCV2023 Oral] RoadNetworkTRansformer & [AAAI 2024] LaneGraph2Seq
Official repository of S-Agents: Self-organizing Agents in Open-ended Environment
[ICLR 2023] S-NeRF: Neural Radiance Fields for Street Views
[ICLR 2023] SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation
Automated dense category annotation engine that serves as the initial semantic labeling for the Segment Anything dataset (SA-1B).
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
[NeurIPS 2021 Spotlight] & [IJCV 2024] SOFT: Softmax-free Transformer with Linear Complexity
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