6.2k citations · 14.2k across the 134 of their papers we have counts for
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Combining the Best of Graphical Models and ConvNets for Semantic Segmentation
Michael Cogswell, Xiao Lin, Senthil Purushwalkam +1
We present a two-module approach to semantic segmentation that incorporates Convolutional Networks (CNNs) and Graphical Models. Graphical models are used to generate a small (5-30)…
Candidate Constrained CRFs for Loss-Aware Structured Prediction
Faruk Ahmed, Daniel Tarlow, Dhruv Batra
When evaluating computer vision systems, we are often concerned with performance on a task-specific evaluation measure such as the Intersection-Over-Union score used in the PASCAL…
Submodular meets Structured: Finding Diverse Subsets in Exponentially-Large Structured Item Sets
Adarsh Prasad, Stefanie Jegelka, Dhruv Batra
To cope with the high level of ambiguity faced in domains such as Computer Vision or Natural Language processing, robust prediction methods often search for a diverse set of high-q…
Optimizing the For loop: Comparison of For loop and micro For loop
Rishabh Jain, Sakshi Gupta
Looping is one of the fundamental logical instructions used for repeating a block of code. It is used in programs across all programming languages. Traditionally, in languages like…
Clear, Concise and Effective UI: Opinion and Suggestions
Rishabh Jain, Rupanta Rwiteej Dutta, Rajat Tandon
The most important aspect of any Software is the operability for the intended audience. This factor of operability is encompassed in the user interface, which serves as the only wi…
Mining and Analyzing Twitter trends: Frequency based ranking of descriptive Tweets
Rishabh Jain, Abhishek B. S., Satvik Jagannath
One of the major sources of trending news, events and opinion in the current age is micro blogging. Twitter, being one of them, is extensively used to mine data about public respon…
A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems
Jörg H. Kappes, Bjoern Andres, Fred A. Hamprecht +10
Szeliski et al. published an influential study in 2006 on energy minimization methods for Markov Random Fields (MRF). This study provided valuable insights in choosing the best opt…