activity
20122017
most citedUnsupervised learning of object semantic parts from internal states of CNNs by population encoding

37 citations · 57 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2017★ 16 cited

Visual Concepts and Compositional Voting

Jianyu Wang, Zhishuai Zhang, Cihang Xie +5

It is very attractive to formulate vision in terms of pattern theory \cite{Mumford2010pattern}, where patterns are defined hierarchically by compositions of elementary building blo…

cs.CV2017

Deep Residual Learning for Instrument Segmentation in Robotic Surgery

Daniil Pakhomov, Vittal Premachandran, Max Allan +2

Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery. In the majority of cases, the…

cs.CV2015★ 3 cited

PASCAL Boundaries: A Class-Agnostic Semantic Boundary Dataset

Vittal Premachandran, Boyan Bonev, Alan L. Yuille

In this paper, we address the boundary detection task motivated by the ambiguities in current definition of edge detection. To this end, we generate a large database consisting of…

cs.LG2015★ 37 cited

Unsupervised learning of object semantic parts from internal states of CNNs by population encoding

Jianyu Wang, Zhishuai Zhang, Cihang Xie +2

We address the key question of how object part representations can be found from the internal states of CNNs that are trained for high-level tasks, such as object classification. T…

cs.CV2012★ 1 cited

Perceptually Motivated Shape Context Which Uses Shape Interiors

Vittal Premachandran, Ramakrishna Kakarala

In this paper, we identify some of the limitations of current-day shape matching techniques. We provide examples of how contour-based shape matching techniques cannot provide a goo…