11 citations · 24 across the 4 of their papers we have counts for
8 papers
Unifying (Machine) Vision via Counterfactual World Modeling
Daniel M. Bear, Kevin Feigelis, Honglin Chen +5
Leading approaches in machine vision employ different architectures for different tasks, trained on costly task-specific labeled datasets. This complexity has held back progress in…
Unsupervised Segmentation in Real-World Images via Spelke Object Inference
Honglin Chen, Rahul Venkatesh, Yoni Friedman +4
Self-supervised, category-agnostic segmentation of real-world images is a challenging open problem in computer vision. Here, we show how to learn static grouping priors from motion…
Deep Implicit Surface Point Prediction Networks
Rahul Venkatesh, Tejan Karmali, Sarthak Sharma +4
Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit repr…
DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces
Rahul Venkatesh, Sarthak Sharma, Aurobrata Ghosh +2
High fidelity representation of shapes with arbitrary topology is an important problem for a variety of vision and graphics applications. Owing to their limited resolution, classic…
Class-Incremental Domain Adaptation
Jogendra Nath Kundu, Rahul Mysore Venkatesh, Naveen Venkat +2
We introduce a practical Domain Adaptation (DA) paradigm called Class-Incremental Domain Adaptation (CIDA). Existing DA methods tackle domain-shift but are unsuitable for learning…
Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
Jogendra Nath Kundu, Ambareesh Revanur, Govind Vitthal Waghmare +2
We present a deployment friendly, fast bottom-up framework for multi-person 3D human pose estimation. We adopt a novel neural representation of multi-person 3D pose which unifies t…
Appearance Consensus Driven Self-Supervised Human Mesh Recovery
Jogendra Nath Kundu, Mugalodi Rakesh, Varun Jampani +2
We present a self-supervised human mesh recovery framework to infer human pose and shape from monocular images in the absence of any paired supervision. Recent advances have shifte…
Segmenting Ships in Satellite Imagery With Squeeze and Excitation U-Net
Venkatesh R, Anand Metha
The ship-detection task in satellite imagery presents significant obstacles to even the most state of the art segmentation models due to lack of labelled dataset or approaches whic…