146 citations · 445 across the 13 of their papers we have counts for
16 papers
Unsupervised Monocular Depth Learning in Dynamic Scenes
Hanhan Li, Ariel Gordon, Hang Zhao +2
We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consiste…
What Matters in Unsupervised Optical Flow
Rico Jonschkowski, Austin Stone, Jonathan T. Barron +3
We systematically compare and analyze a set of key components in unsupervised optical flow to identify which photometric loss, occlusion handling, and smoothness regularization is…
Improving Semantic Segmentation through Spatio-Temporal Consistency Learned from Videos
Ankita Pasad, Ariel Gordon, Tsung-Yi Lin +1
We leverage unsupervised learning of depth, egomotion, and camera intrinsics to improve the performance of single-image semantic segmentation, by enforcing 3D-geometric and tempora…
Taskology: Utilizing Task Relations at Scale
Yao Lu, Sören Pirk, Jan Dlabal +6
Many computer vision tasks address the problem of scene understanding and are naturally interrelated e.g. object classification, detection, scene segmentation, depth estimation, et…
Detecting Deficient Coverage in Colonoscopies
Daniel Freedman, Yochai Blau, Liran Katzir +8
Colonoscopy is the tool of choice for preventing Colorectal Cancer, by detecting and removing polyps before they become cancerous. However, colonoscopy is hampered by the fact that…
Computationally Efficient Neural Image Compression
Nick Johnston, Elad Eban, Ariel Gordon +1
Image compression using neural networks have reached or exceeded non-neural methods (such as JPEG, WebP, BPG). While these networks are state of the art in ratedistortion performan…