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The Hong Kong University of Science and Technology
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WAT3R achieves high-quality underwater 3D reconstruction by effectively adapting to imaging degradation in a single forward pass, outperforming existing methods.
Achieving a new state-of-the-art FID score of 1.94 in pixel-space autoregressive image generation, PRA redefines the capabilities of pixel-based models.
E(3) equivariance and derivative-aware training enables a GNN to predict XANES spectra with high fidelity, opening the door to ML-assisted spectroscopy and accelerated materials discovery.
Unlock real-time, holistic 3D tracking of every pixel in a video with Track4World, a feedforward model that leapfrogs past slow, optimization-based methods.
