Search Results for author: Anchit Gupta

Found 19 papers, 7 papers with code

3DGen: Triplane Latent Diffusion for Textured Mesh Generation

no code implementations9 Mar 2023 Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, Barlas Oğuz

We take another step along this direction, combining these developments in a two-step pipeline consisting of 1) a triplane VAE which can learn latent representations of textured meshes and 2) a conditional diffusion model which generates the triplane features.

Image Generation Texture Synthesis

CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic Furniture Embedding

no code implementations7 Mar 2023 Jingyu Liu, Wenhan Xiong, Ian Jones, Yixin Nie, Anchit Gupta, Barlas Oğuz

Whether heuristic or learned, these methods ignore instance-level visual attributes of objects, and as a result may produce visually less coherent scenes.

Indoor Scene Synthesis Scene Generation

Unsupervised Audio-Visual Lecture Segmentation

no code implementations29 Oct 2022 Darshan Singh S, Anchit Gupta, C. V. Jawahar, Makarand Tapaswi

We formulate lecture segmentation as an unsupervised task that leverages visual, textual, and OCR cues from the lecture, while clip representations are fine-tuned on a pretext self-supervised task of matching the narration with the temporally aligned visual content.

Navigate Optical Character Recognition (OCR)

Compressing Video Calls using Synthetic Talking Heads

no code implementations7 Oct 2022 Madhav Agarwal, Anchit Gupta, Rudrabha Mukhopadhyay, Vinay P. Namboodiri, C V Jawahar

We use a state-of-the-art face reenactment network to detect key points in the non-pivot frames and transmit them to the receiver.

Face Reenactment Talking Head Generation +1

A Study on the Efficiency and Generalization of Light Hybrid Retrievers

no code implementations4 Oct 2022 Man Luo, Shashank Jain, Anchit Gupta, Arash Einolghozati, Barlas Oguz, Debojeet Chatterjee, Xilun Chen, Chitta Baral, Peyman Heidari

Driven by this question, we leverage an indexing-efficient dense retriever (i. e. DrBoost) and introduce a LITE retriever that further reduces the memory of DrBoost.

Adversarial Attack Contrastive Learning +1

Retrieve-and-Fill for Scenario-based Task-Oriented Semantic Parsing

no code implementations2 Feb 2022 Akshat Shrivastava, Shrey Desai, Anchit Gupta, Ali Elkahky, Aleksandr Livshits, Alexander Zotov, Ahmed Aly

We tackle this problem by introducing scenario-based semantic parsing: a variant of the original task which first requires disambiguating an utterance's "scenario" (an intent-slot template with variable leaf spans) before generating its frame, complete with ontology and utterance tokens.

Retrieval Semantic Parsing

Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?

2 code implementations13 Oct 2021 Xilun Chen, Kushal Lakhotia, Barlas Oğuz, Anchit Gupta, Patrick Lewis, Stan Peshterliev, Yashar Mehdad, Sonal Gupta, Wen-tau Yih

Despite their recent popularity and well-known advantages, dense retrievers still lag behind sparse methods such as BM25 in their ability to reliably match salient phrases and rare entities in the query and to generalize to out-of-domain data.

Open-Domain Question Answering Passage Retrieval +1

MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark

no code implementations EACL 2021 Haoran Li, Abhinav Arora, Shuohui Chen, Anchit Gupta, Sonal Gupta, Yashar Mehdad

Scaling semantic parsing models for task-oriented dialog systems to new languages is often expensive and time-consuming due to the lack of available datasets.

Benchmarking Semantic Parsing +1

Better Fine-Tuning by Reducing Representational Collapse

3 code implementations ICLR 2021 Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta, Naman Goyal, Luke Zettlemoyer, Sonal Gupta

Although widely adopted, existing approaches for fine-tuning pre-trained language models have been shown to be unstable across hyper-parameter settings, motivating recent work on trust region methods.

Abstractive Text Summarization Cross-Lingual Natural Language Inference

Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

no code implementations11 Nov 2019 Ajay Mandlekar, Jonathan Booher, Max Spero, Albert Tung, Anchit Gupta, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei

We evaluate the quality of our platform, the diversity of demonstrations in our dataset, and the utility of our dataset via quantitative and qualitative analysis.

Robot Manipulation

RoboTurk: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

no code implementations7 Nov 2018 Ajay Mandlekar, Yuke Zhu, Animesh Garg, Jonathan Booher, Max Spero, Albert Tung, Julian Gao, John Emmons, Anchit Gupta, Emre Orbay, Silvio Savarese, Li Fei-Fei

Imitation Learning has empowered recent advances in learning robotic manipulation tasks by addressing shortcomings of Reinforcement Learning such as exploration and reward specification.

Imitation Learning

Stochastic Shortest Path with Energy Constraints in POMDPs

no code implementations24 Feb 2016 Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelík, Anchit Gupta, Petr Novotný

Finally, we show experimentally that our algorithm performs well and computes succinct policies on a number of POMDP instances from the literature that were naturally enhanced with energy levels.

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