Presenting BoundaryNet - a resizing-free approach for high-precision weakly supervised document layout parsing. BoundaryNet will be an ORAL presentation (Oral Session 3) today at @icdar2021 . Project page: ihdia.iiit.ac.in/BoundaryNet/ . Details 👇 Precise boundary annotations can be crucial for downstream applications which rely on region-class semantics. Some document collections contain irregular and overlapping region instances. Fully automatic approaches require resizing and often produce suboptimal parsing results.

📢 In our #ACMMM21 paper, we highlight issues with training and evaluation of 𝗰𝗿𝗼𝘄𝗱 𝗰𝗼𝘂𝗻𝘁𝗶𝗻𝗴 deep networks. 🧵👇 For far too long, 𝗰𝗿𝗼𝘄𝗱 𝗰𝗼𝘂𝗻𝘁𝗶𝗻𝗴 works in #CVPR, #AAAI, #ICCV, #NeurIPS have reported only MAE, but not standard deviation.

📢 Introducing SynSE, a language-guided approach for generalized zero shot learning of pose-based action representations! Great effort by @bublaasaur and @divyanshu1709 #actionrecognition

Paper: arxiv.org/abs/2101.11530…
Code: github.com/skelemoa/synse…

🧵👇 For enabling compositional generalization to novel action-object combinations, the action description is transformed into individual Part-of-Speech based embeddings.