230 citations · 381 across the 18 of their papers we have counts for
27 papers · 1 filter
Non-deep Networks
Ankit Goyal, Alexey Bochkovskiy, Jia Deng +1
Depth is the hallmark of deep neural networks. But more depth means more sequential computation and higher latency. This begs the question -- is it possible to build high-performin…
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching
Lahav Lipson, Zachary Teed, Jia Deng
We introduce RAFT-Stereo, a new deep architecture for rectified stereo based on the optical flow network RAFT. We introduce multi-level convolutional GRUs, which more efficiently p…
Dynamically Grown Generative Adversarial Networks
Lanlan Liu, Yuting Zhang, Jia Deng +1
Recent work introduced progressive network growing as a promising way to ease the training for large GANs, but the model design and architecture-growing strategy still remain under…
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu +2
Processing point cloud data is an important component of many real-world systems. As such, a wide variety of point-based approaches have been proposed, reporting steady benchmark i…
Tangent Space Backpropagation for 3D Transformation Groups
Zachary Teed, Jia Deng
We address the problem of performing backpropagation for computation graphs involving 3D transformation groups SO(3), SE(3), and Sim(3). 3D transformation groups are widely used in…
Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3D
Ankit Goyal, Kaiyu Yang, Dawei Yang +1
Understanding spatial relations (e.g., "laptop on table") in visual input is important for both humans and robots. Existing datasets are insufficient as they lack large-scale, high…