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20192025
most citedLearning to Generate Synthetic Data via Compositing

6 citations · 6 across the 6 of their papers we have counts for

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10 papers · 1 filter

cs.CV2025

PICO: Reconstructing 3D People In Contact with Objects

Alpár Cseke, Shashank Tripathi, Sai Kumar Dwivedi +4

Recovering 3D Human-Object Interaction (HOI) from single color images is challenging due to depth ambiguities, occlusions, and the huge variation in object shape and appearance. Th…

cs.CV2025

InteractVLM: 3D Interaction Reasoning from 2D Foundational Models

Sai Kumar Dwivedi, Dimitrije Antić, Shashank Tripathi +4

We introduce InteractVLM, a novel method to estimate 3D contact points on human bodies and objects from single in-the-wild images, enabling accurate human-object joint reconstructi…

cs.CV2024

SDFit: 3D Object Pose and Shape by Fitting a Morphable SDF to a Single Image

Dimitrije Antić, Georgios Paschalidis, Shashank Tripathi +3

Recovering 3D object pose and shape from a single image is a challenging and ill-posed problem. This is due to strong (self-)occlusions, depth ambiguities, the vast intra- and inte…

cs.CV2024

HUMOS: Human Motion Model Conditioned on Body Shape

Shashank Tripathi, Omid Taheri, Christoph Lassner +3

Generating realistic human motion is essential for many computer vision and graphics applications. The wide variety of human body shapes and sizes greatly impacts how people move.…

cs.CV2022

MIME: Human-Aware 3D Scene Generation

Hongwei Yi, Chun-Hao P. Huang, Shashank Tripathi +3

Generating realistic 3D worlds occupied by moving humans has many applications in games, architecture, and synthetic data creation. But generating such scenes is expensive and labo…

cs.CV2022

PERI: Part Aware Emotion Recognition In The Wild

Akshita Mittel, Shashank Tripathi

Emotion recognition aims to interpret the emotional states of a person based on various inputs including audio, visual, and textual cues. This paper focuses on emotion recognition…