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pro vyhledávání: '"TIWARI, ASHISH"'
Neural radiance fields (NeRF) have exhibited highly photorealistic rendering of novel views through per-scene optimization over a single 3D scene. With the growing popularity of NeRF and its variants, they have become ubiquitous and have been identif
Externí odkaz:
http://arxiv.org/abs/2411.19903
Art has long been a medium for individuals to engage with the world. Scribble art, a form of abstract visual expression, features spontaneous, gestural strokes made with pens or brushes. These dynamic and expressive compositions, created quickly and
Externí odkaz:
http://arxiv.org/abs/2411.08673
Photometric stereo typically demands intricate data acquisition setups involving multiple light sources to recover surface normals accurately. In this paper, we propose MERLiN, an attention-based hourglass network that integrates single image-based i
Externí odkaz:
http://arxiv.org/abs/2409.00674
Photometric stereo is a powerful method for obtaining per-pixel surface normals from differently illuminated images of an object. While several methods address photometric stereo with different image (or light) counts ranging from one to two to a hun
Externí odkaz:
http://arxiv.org/abs/2409.02716
Autor:
Tiwari, Ashish, Raman, Shanmuganathan
We present a novel inverse rendering-based framework to estimate the 3D shape (per-pixel surface normals and depth) of objects and scenes from single-view polarization images, the problem popularly known as Shape from Polarization (SfP). The existing
Externí odkaz:
http://arxiv.org/abs/2407.09294
Autor:
Chopra, Bhavya, Singha, Ananya, Fariha, Anna, Gulwani, Sumit, Parnin, Chris, Tiwari, Ashish, Henley, Austin Z.
Large Language Models (LLMs) are being increasingly employed in data science for tasks like data preprocessing and analytics. However, data scientists encounter substantial obstacles when conversing with LLM-powered chatbots and acting on their sugge
Externí odkaz:
http://arxiv.org/abs/2310.16164
Information retrieval involves selecting artifacts from a corpus that are most relevant to a given search query. The flavor of retrieval typically used in classical applications can be termed as homogeneous and relaxed, where queries and corpus eleme
Externí odkaz:
http://arxiv.org/abs/2310.05380
Denial Constraint (DC) is a well-established formalism that captures a wide range of integrity constraints commonly encountered, including candidate keys, functional dependencies, and ordering constraints, among others. Given their significance, ther
Externí odkaz:
http://arxiv.org/abs/2309.12436
Autor:
Gupta, Priyanshu, Khare, Avishree, Bajpai, Yasharth, Chakraborty, Saikat, Gulwani, Sumit, Kanade, Aditya, Radhakrishna, Arjun, Soares, Gustavo, Tiwari, Ashish
Developers expend a significant amount of time in editing code for a variety of reasons such as bug fixing or adding new features. Designing effective methods to predict code edits has been an active yet challenging area of research due to the divers
Externí odkaz:
http://arxiv.org/abs/2305.14129
Autor:
Khatry, Anirudh, Cahoon, Joyce, Henkel, Jordan, Deep, Shaleen, Emani, Venkatesh, Floratou, Avrilia, Gulwani, Sumit, Le, Vu, Raza, Mohammad, Shi, Sherry, Singh, Mukul, Tiwari, Ashish
Creating programs to correctly manipulate data is a difficult task, as the underlying programming languages and APIs can be challenging to learn for many users who are not skilled programmers. Large language models (LLMs) demonstrate remarkable poten
Externí odkaz:
http://arxiv.org/abs/2305.01598