Lu Fang
Professor
Works on computational imaging and vision, gigapixel and light-field imaging, and photonic AI chips.
Lu Fang's lab at Tsinghua works on computational imaging & photography. 37 papers since 2023, 20 at top venues, mostly CVPR and Nature. 12 PhD students and 3 master's students. 31 alumni. Applications close .
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 54%
- PhD students
- 12
- MS students
- 3
- alumni listed
- 31
Papers by yearfrom the lab homepage, 2023–2026
- 6 papers2026 · T1 2 · collecting
- 7 papers2025 · T1 2
- 11 papers2024 · T1 7
- 13 papers2023 · T1 9
T1 venuesOtherVenues: CVPR, Nature, Nature Communications, ICCV, Nature Methods
Research focuspaper titles that use each topic's words
- photonic10 papers
- Computational imaging & photography3 papers
- imaging3 papers
- light-field0 papers
- chips0 papers
Paper list
From the lab homepage.
20266 papers
- Nature Communications (T1)A skin-conformal rigid-in-soft array-based imaging system
- Nature SensorsFully in-memory photonic computing
- Nature SensorsMulti-responsive retinomorphic sensor for reconfigurable optoelectronic computing
- Nature Computational SciencePhotonic neuromorphic learning via generalized in situ physical gradient descent
- IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), JanRealLiFe: Real-Time Light Field Reconstruction via Hierarchical Sparse Gradient Descent
- Nature (T1)Sub-second volumetric 3D printing by synthesis of holographic light fields
20257 papers
- Nature Computational ScienceA complete photonic integrated neuron for nonlinear all-optical computing
- OpticaComputational optical imaging: on the convergence of physical and digital layers
- Nature PhotonicsDiffractive tensorized unit for million-TOPS general-purpose computing
- Nature NanotechnologyFully integrated multi-mode optoelectronic memristor array for diversified in-sensor computing
- Nature Communications (T1)Hundred-layer photonic deep learning
- Nature (T1)Integrated lithium niobate photonics for sub-ångström snapshot spectroscopy
- NanophotonicsReliable, efficient, and scalable photonic inverse design empowered by physics-inspired deep learning
202411 papers
- Nature PhotonicsDirect observation of atmospheric turbulence with a video-rate wide-field wavefront sensor
- Nature (T1)Fully forward mode training for optical neural networks
- CVPR (T1)GigaTraj: Predicting Long-term Trajectories of Hundreds of Pedestrians in Gigapixel Complex Scenes
- Science (T1)Large-scale photonic chiplet Taichi empowers 160-TOPS/W artificial general intelligence
- Science AdvancesNanowatt all-optical 3D perception for mobile robotics
- CVPR (T1)OmniSeg3D: Omniversal 3D Segmentation via Hierarchical Contrastive Learning
- OSA OpticaParallel photonic chip for nanosecond end-to-end image processing, transmission, and reconstruction
- Light: Science & ApplicationsPhotonic neuromorphic architecture for tens-of-task lifelong learning
- CVPR (T1)SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction
- CVPR (T1)When Visual Grounding Meets Gigapixel-level Large-scale Scenes: Benchmark and Approach
- CVPR (T1)XScale-NVS: Cross-Scale Novel View Synthesis with Hash Featurized Manifold
202313 papers
- Nature (T1)All-analog photoelectronic chip for high-speed vision tasks
- Proceedings of the International Conference on Machine Learning (ICML).Boosting Graph Contrastive Learning via Graph Contrastive Saliency
- CVPR (T1)Crowd3D: Towards Hundreds of People Reconstruction from a Single Image
- CVPR (T1)DartBlur: Privacy Preservation with Detection Artifact Suppression
- IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), OctGiganticNVS: Gigapixel Large-scale Neural Rendering with Implicit Meta-deformed Manifold
- Nature Communications (T1)Large depth-of-field ultra-compact micro-scope by progressive optimization and deep learning
- ICCV (T1)PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis
- Science AdvancesPhotonic unsupervised learning variational autoencoder for high-throughput and low-latency image transmission
- Nature Methods (T1)Rapid detection of neurons in widefield calcium imaging datasets after training with synthetic data
- ICCV (T1)RealGraph: A Multiview Dataset for 4D Real-world Context Graph Generation
- ICCV (T1)SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation
- Nature Communications (T1)Training large-scale optoelectronic neural networks with dual-neuron optical-artificial learning
Where alumni went31 listed
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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